Last updated: 2021-10-08
Checks: 6 1
Knit directory: Bonfini_eLife_2021/
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| absolute | relative |
|---|---|
| F:/Dropbox/Github/Bonfini_eLife_2021/data/ | data |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/1A.jpg | data/1A.jpg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/1C.jpg | data/1C.jpg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/1D.jpg | data/1D.jpg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_1.tiff | data/Figures/Figure_1.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_1S1.tiff | data/Figures/Figure_1S1.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/1- S2A.jpg | data/1- S2A.jpg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig1S2B.jpeg | data/Plot_Fig1S2B.jpeg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_1S2.tiff | data/Figures/Figure_1S2.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/1 - S3.jpg | data/1 - S3.jpg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_1S3.tiff | data/Figures/Figure_1S3.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig2A.jpeg | data/Plot_Fig2A.jpeg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Nutri_geo_graph.jpg | data/Nutri_geo_graph.jpg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_2.tiff | data/Figures/Figure_2.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig2-S1B.jpeg | data/Plot_Fig2-S1B.jpeg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_2S1.tiff | data/Figures/Figure_2S1.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_2S2.tiff | data/Figures/Figure_2S2.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_3.tiff | data/Figures/Figure_3.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_3S1.tiff | data/Figures/Figure_3S1.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_4S1.tiff | data/Figures/Figure_4S1.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_4S2.tiff | data/Figures/Figure_4S2.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/5F | data/5F |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/5J | data/5J |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_5.tiff | data/Figures/Figure_5.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_5S1.tiff | data/Figures/Figure_5S1.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2A.jpg | data/5 - S2A.jpg |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2A | data/5 - S2A |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_5S2.tiff | data/Figures/Figure_5S2.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_6.tiff | data/Figures/Figure_6.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_6S1.tiff | data/Figures/Figure_6S1.tiff |
| F:/Dropbox/Github/Bonfini_eLife_2021/data/7B.jpg | data/7B.jpg |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_7S1.tiff | data/Figures/Figure_7S1.tiff |
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| F:/Dropbox/Github/Bonfini_eLife_2021/data/Figures/Figure_7S3.tiff | data/Figures/Figure_7S3.tiff |
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|---|---|---|---|---|
| Rmd | 8fa9317 | dduneau | 2021-10-08 | Bonfini eLife 2021 project |
library(devtools)
library(reshape2)
library(lattice)
library(MASS)
library(car)
library(lmtest)
library(ggplot2)
library(survival)
library(plotrix)
library(grid)
library(gridExtra)
library(agricolae)
library(nparLD)
library(psych)
library(doBy)
library(xlsxjars)
library(xlsx)
library(dplyr)
library(stringr)
library(scales)
library(tidyr)
library(phia)
library(data.table)
library(spaMM)
library(lme4)
library(fields)
library(EBImage)
library(gplots)
library(RColorBrewer)
library(gridGraphics)
library(fields)
library(multcomp)
library(ggrepel)
library(metR)
library(forcats)
library(ggh4x)#remotes::install_github("teunbrand/ggh4x")
library(GenomicRanges)
library(DESeq2)
library(RColorBrewer)
library(coxme)
library(ggplotify)
#library(base2grob)
library(knitr)
library(kableExtra)
library(plotfunctions)
library(ggsignif)
#Function to include factor that are NOT in a list
'%!in%' = function(x,y)!('%in%'(x,y))
#Function to Grab graph and display it as a ggplot graph
grab_grob = function(){
grid.echo()
grid.grab()
}
#Function to calculate standard deviaion
sd = function(x) sqrt(var(x,na.rm=T))
#Function to calculate standard error
se = function(x) sqrt(var(x,na.rm=T)/length(x))
# Function to graph survival with ggplot and displaying the checkpoints
ggplotprep2 <- function(x, times){
#spreading the surfit dataframe into dataframe per day.
d <- data.frame(condition=rep(names(x$strata), x$strata), time=x$time, survival=x$surv, upper=x$upper, lower=x$lower)
# function to add time point 0
fillup0 <- function(s) rbind(c(condition=s, time=0, survival=1, upper=1, lower=1), d[d$condition==s, ], deparse.level = 0)
# function to determine the missing time points
indexes <- function(x, time) {
if(x%in%time) return(x)
return(time[which.min(abs(time[time<x]-x))])
}
#Function to complete the missing time points
fillup <- function(s) {
d.temp <- d[d$condition==s, ]
time <- as.numeric(d.temp$time)
id <- sapply(times, indexes, time=time)
d.temp <- d.temp[match(id, time), ]
d.temp$time <- times
return(d.temp)
}
if(times[1]==0) d <- do.call("rbind", sapply(names(x$strata), fillup0, simplify=F))
d <- do.call("rbind", sapply(names(x$strata), fillup, simplify=F))
clean.name <- function(name) unlist(lapply(strsplit(as.character(name), split="="), function(x) x[2]))
d <- data.frame(Condition=clean.name(d$condition), Time=as.numeric(d$time), Survival=as.numeric(d$survival), upper=as.numeric(d$upper), lower=as.numeric(d$lower))
return(d)
}
#function to select colours for GF-style plot (function mapping colors)
seeMahPal <- function(x, pal){
pal[round(x)]
}
#a function to take x,y,z
#and return a GF-style plot with points per diet
geomPlotta <- function(x,y,z,alf,...){
dat <- data.frame(x=x, y=y, z=z)
d.means <- aggregate(z ~ x * y, dat, mean)
surf.te <- Tps(cbind(dat$x, dat$y), dat$z, lambda = 0)
experiColours <- data.frame(z=d.means$z, rank=rank(d.means$z), rnd=round(d.means$z), rankRnd=rank(round(d.means$z)))
mahPal <- colorRampPalette(c("darkblue", "blue", "turquoise", "yellow", "orange", "red", "darkred"))(max(experiColours$rank)) #Decide colors
d.means$colour <- seeMahPal(x=d.means$z, pal=mahPal)
surface(predictSurface(surf.te, extrap=F), col=alpha(mahPal, alf), ...)
points(d.means$x, d.means$y, bg=seeMahPal(x=experiColours$rank, pal=mahPal), col="white", pch=21, cex=1, ...)
}
left = function(text, num_char) {
substr(text, 1, num_char)
}
mid = function(text, start_num, num_char) {
substr(text, start_num, start_num + num_char - 1)
}
right = function(text, num_char) {
substr(text, nchar(text) - (num_char-1), nchar(text))
}SuperSmallfont= 6
xSmallfont = 8
Smallfont= 10
Mediumfont= 12
Largefont= 14
verylargefont = 16
pointsize= 0.7
linesize=0.35
meansize = 1.5
Margin=c(0,0,0,0)
fontsizeaxes = 14
fontsizeaxes2 = 10
palette_diet_2 = c("#FFB4B4", "#C3E6FC")
palette_component_3 = c("#f4ead0","#2d5ad7","gold")
palette_mean = c("yellow","green","red","white","magenta","skyblue", "blue", "deeppink", "gold")
cbbPalette_4 = c("#BDE6BD", "#C3E6FC", "#FFE5E5", "#E5E5FF") #Green eclosion, HY, HYtoHS, HStoHY
cbbHS_HStoHY = c("#FFB4B4","#E5E5FF")
cbbHY_HYtoHS = c("#C3E6FC","#FFE5E5")
Warning: The above code chunk cached its results, but it won’t be re-run if previous chunks it depends on are updated. If you need to use caching, it is highly recommended to also set knitr::opts_chunk$set(autodep = TRUE) at the top of the file (in a chunk that is not cached). Alternatively, you can customize the option dependson for each individual chunk that is cached. Using either autodep or dependson will remove this warning. See the knitr cache options for more details.
path.to.data = "F:/Dropbox/Github/Bonfini_eLife_2021/data/"
rm(d,path)
d = list()
path = list()
for(f in list.files(path=path.to.data,pattern="*.csv$",recursive=T,full.names=T)) {
nom = gsub(".*/(.*).csv","\\1",f)
cat(nom,"\n")
path[[nom]] = gsub("(.*)/.*csv","\\1/",f)
d[[nom]] = read.table(f,header=T,sep=",")
}
Warning: The above code chunk cached its results, but it won’t be re-run if previous chunks it depends on are updated. If you need to use caching, it is highly recommended to also set knitr::opts_chunk$set(autodep = TRUE) at the top of the file (in a chunk that is not cached). Alternatively, you can customize the option dependson for each individual chunk that is cached. Using either autodep or dependson will remove this warning. See the knitr cache options for more details.
wolb = d[["DGRP_wolbachia_DFD"]]
colnames(wolb) = c("dgrp_id", "wolbachia")Error in `colnames<-`(`*tmp*`, value = c("dgrp_id", "wolbachia")): tentative de modification de 'colnames' sur un objet ayant moins de deux dimensionswolb$dgrp_id = gsub("line_", "DGRP-", wolb$dgrp_id)
weight = d[["weights"]]
decode = d[["stockDecode"]]
weight$mg = weight$weightPerFlyGram * 1000
weight$diet = tolower(weight$diet)
decode$shortID = as.factor(as.character(decode$shortID))
weight$stockNumber = as.factor(as.character(weight$dgrp))
weight = merge(weight, decode, by.x="stockNumber", by.y="shortID")
colnames(weight) = tolower(colnames(weight))
weight = weight[,which(!colnames(weight) %in% c("stockNumber", "dgrp.x"))]
colnames(weight)[which(colnames(weight) == "dgrp.y")] = "dgrp"
weight$dgrp_number = substr(as.character(weight$dgrp), 1, 3)
weight$dgrpDiet = factor(paste(weight$dgrp_number, weight$diet, sep="_"))
tab_GWAS_gut = d[["1F - G"]]
#edit the data
table(complete.cases(tab_GWAS_gut))Error in complete.cases(tab_GWAS_gut): aucune entrée n'a déterminé le nombre de cas#str(tab_GWAS_gut)
tab_GWAS_gut= mutate_if(tab_GWAS_gut,is.integer,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"colnames(tab_GWAS_gut) = tolower(colnames(tab_GWAS_gut))Error in `colnames<-`(`*tmp*`, value = character(0)): tentative de modification de 'colnames' sur un objet ayant moins de deux dimensionstab_GWAS_gut = tab_GWAS_gut[,!colnames(tab_GWAS_gut) %in% c("notes", "image", "bloomington_id")]
#remove the samples that subsequently proved crazy
tab_GWAS_gut = subset(tab_GWAS_gut, anteriorwidth < 1000)Error in subset.default(tab_GWAS_gut, anteriorwidth < 1000): objet 'anteriorwidth' introuvabletab_GWAS_gut = subset(tab_GWAS_gut, middlelength < 1500)Error in subset.default(tab_GWAS_gut, middlelength < 1500): objet 'middlelength' introuvable#remove lines that don't appear in both diets
dgrpLines = levels(tab_GWAS_gut$dgrp_number)
yDat = droplevels(subset(tab_GWAS_gut, diet=="y"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : objet 'diet' introuvablexDat = droplevels(subset(tab_GWAS_gut, diet=="x"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : objet 'diet' introuvablelength(dgrpLines)
dgrpLines = dgrpLines[dgrpLines %in% yDat$dgrp_number]Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'table' lors de la s�lection d'une m�thode pour la fonction '%in%' : objet 'yDat' introuvable#length(dgrpLines)
dgrpLines = dgrpLines[dgrpLines %in% xDat$dgrp_number]Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'table' lors de la s�lection d'une m�thode pour la fonction '%in%' : objet 'xDat' introuvable#length(dgrpLines)
tab_GWAS_gut = droplevels(subset(tab_GWAS_gut, dgrp_number %in% dgrpLines))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction '%in%' : objet 'dgrp_number' introuvableyDat = droplevels(subset(yDat, dgrp_number %in% dgrpLines))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'yDat' introuvablexDat = droplevels(subset(xDat, dgrp_number %in% dgrpLines))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'xDat' introuvable#link up Wolbachia
tab_GWAS_gut = merge(tab_GWAS_gut, wolb, by="dgrp_id")Error in fix.by(by.x, x): 'by' doit spécifier une colonne unique correctetab_GWAS_gut= mutate_if(tab_GWAS_gut,is.character,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"
Warning: The above code chunk cached its results, but it won’t be re-run if previous chunks it depends on are updated. If you need to use caching, it is highly recommended to also set knitr::opts_chunk$set(autodep = TRUE) at the top of the file (in a chunk that is not cached). Alternatively, you can customize the option dependson for each individual chunk that is cached. Using either autodep or dependson will remove this warning. See the knitr cache options for more details.
Illustration of general dietary treatment design. Flies were reared on pre-experiment diet during development. At eclosion, flies were allocated to either HS or HY before midgut dissection at 5 days post eclosion.
img1A = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/1A.jpg") Error in transpose(y): object is NULLgob_imageFig1A = rasterGrob(img1A)Error in rasterGrob(img1A): objet 'img1A' introuvablegrid.draw(gob_imageFig1A)Error in grid.draw(gob_imageFig1A): objet 'gob_imageFig1A' introuvableNutritional composition (proteins, carbohydrates, and lipids) of the two isocaloric diets used as a basis for this study as calories per liter of food: enriched in sugars (High sugar, HS) or yeast (High yeast, HY).
general_info_diet =d[["1B"]]
general_info_diet = mutate_if(general_info_diet,is.character,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"general_info_diet$Component <- factor(general_info_diet$Component, levels = c("Lipids","Proteins","Carbohydrates"))
Limits = c("Lipids","Proteins","Carbohydrates")
Labels = c("Lipids","Proteins","Carbohydrates")
Plot_Fig1B=
ggplot(general_info_diet,aes(x=Diet,y=Calories.contributed))+
geom_bar(stat="identity",aes(fill=Component),color="black",width=.90)+
scale_fill_manual(limits=Limits,
values=palette_component_3,
labels=Labels)+
scale_x_discrete("",
limits=c("HS", "HY"),
breaks=c("HS", "HY"))+
scale_y_continuous("Calories/L of food",
breaks=c(seq(0,650,by=200),696))+
theme(axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black"),
axis.line.y = element_line(colour="black"),
axis.ticks.x = element_line(),
axis.ticks.y = element_line(),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
panel.grid = element_blank(),
plot.margin = unit(c(0,0,0,0), "cm"),
legend.direction = "vertical",
legend.box = "vertical",
legend.position = c(0.5,-0.3),
legend.key.height = unit(0.3, "cm"),
legend.key.width= unit(0.3, "cm"),
legend.margin=margin(t=-0.9, r=-0, b=-0, l=-0, unit="cm"),
legend.title = element_blank(),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=xSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside",
panel.background = element_rect(fill="transparent"))+
guides(fill=guide_legend(ncol=1))Error: `data` must be a data frame, or other object coercible by `fortify()`, not a list.Plot_Fig1BError in eval(expr, envir, enclos): objet 'Plot_Fig1B' introuvableCanton S (Cs) flies fed on HS diet (C, first image) have shorter midguts than flies on HY (D, Second image). Complete graphical annotation can be found in manuscript figures
Error in transpose(y): object is NULLError in rasterGrob(img1C): objet 'img1C' introuvableError in grid.draw(gob_imageFig1C): objet 'gob_imageFig1C' introuvableError in transpose(y): object is NULLError in rasterGrob(img1D): objet 'img1D' introuvableError in grid.draw(gob_imageFig1D): objet 'gob_imageFig1D' introuvableQuantification of midgut length for HS vs HY at 5 days post eclosion.
Length_HSHY =
d[["1E - 1S1A"]]%>%
mutate_at(vars(starts_with("Total")),~./1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Total_Length_mm=Total.L,
Total_width_mm=Total.W,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_HSHY%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'Length_HSHY' introuvableAverages <- summarise(group_by(Length_HSHY, Diet), mean = mean(Total_Length_mm, na.rm = TRUE))Error in group_by(Length_HSHY, Diet): objet 'Length_HSHY' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = Length_HSHY)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = Length_HSHY) Error in is.data.frame(data): objet 'Length_HSHY' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = Length_HSHY) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character("HS vs HY"),
Rep = nlevels(Length_HSHY$Repeat),
chi2_LR = format(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_HSHY' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
Limits = c("HS", "HY")
z= max(Length_HSHY$Total_Length_mm)Error in eval(expr, envir, enclos): objet 'Length_HSHY' introuvablePlot_Fig1E=
ggplot(Length_HSHY, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/50) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.3, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 7.3, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS", "HY"),
labels=c("HS", "HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8),
breaks=seq(2,8,by=1),
minor_breaks = seq(3, 7,by= 1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(aspect.ratio=2,
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(Length_HSHY, aes(x = Diet, y = Total_Length_mm)): objet 'Length_HSHY' introuvable#+
# annotate("segment", x = 1, xend = 2, y = 7.2, yend = 7.2,
#colour = "black", size =1.5)
Plot_Fig1EError in eval(expr, envir, enclos): objet 'Plot_Fig1E' introuvableMidgut length response to diet is strongly variable across the DGRP, with HY being generally longer than HS (i.e. the ratio length on HY/length on HS is between 1 and 1.4).
tab_GWAS_gut_mean =
tab_GWAS_gut%>%
group_by(dgrp_number,diet)%>%
summarise(mean_gut_length=mean(totallength,na.rm=T))%>%
spread(diet,mean_gut_length)%>%
dplyr::rename(Mean_length_HS=x,
Mean_length_HY=y)%>%
mutate(Ratio = Mean_length_HY/Mean_length_HS)Error in UseMethod("group_by"): pas de méthode pour 'group_by' applicable pour un objet de classe "NULL"tab_GWAS_gut_se =
tab_GWAS_gut%>%
group_by(dgrp_number,diet)%>%
summarise(se_gut_length = se(totallength))%>%
spread(diet,se_gut_length)%>%
dplyr::rename(SE_length_HS=x,
SE_length_HY=y)Error in UseMethod("group_by"): pas de méthode pour 'group_by' applicable pour un objet de classe "NULL"tab_GWAS_gut_mean= left_join(tab_GWAS_gut_mean,tab_GWAS_gut_se)Error in left_join(tab_GWAS_gut_mean, tab_GWAS_gut_se): objet 'tab_GWAS_gut_mean' introuvablecolors=c("HS"="#FFB4B4","HY"="#C3E6FC","Ratio"="black")
plot_ratio_DGRP=
ggplot(tab_GWAS_gut_mean,aes(x = reorder(dgrp_number,Ratio))) +
geom_point(aes(y=Mean_length_HS/1000,colour="HS"),stat="identity",size=0.7,shape=16)+
geom_errorbar(aes(ymax = (Mean_length_HS+ SE_length_HS)/1000 , ymin = (Mean_length_HS - SE_length_HS)/1000 ,colour="HS"),width=0.1, show.legend=FALSE)+
geom_point(aes(y=Mean_length_HY/1000,colour="HY"),stat="identity",size=0.7,shape=16)+
geom_errorbar(aes(ymax = (Mean_length_HY+ SE_length_HY)/1000 , ymin = (Mean_length_HY - SE_length_HY)/1000 ,colour="HY"),width=0.1, show.legend=FALSE)+
geom_point(aes(y=Ratio*3.9,colour="Ratio"),shape=17,size=0.7)+
geom_hline(yintercept=3.9,linetype=2)+
scale_y_continuous("Midgut length (mm)\n [mean \u00B1 se]",
limits=c(3,7.2),
sec.axis = sec_axis(~./3.9, name = "Ratio (HY/HS)", breaks = seq(0.8,1.8,0.2)))+
scale_x_discrete("DGRP lines",expand=c(0.03,0.03))+
scale_color_manual(values = colors )+
theme(panel.background = element_blank(),
(panel.border = element_blank()),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_blank(),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_blank(),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = c(0.25,0.98),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.4, "cm"),
legend.title = element_blank(),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA))+
guides(color=guide_legend(ncol=3))Error in ggplot(tab_GWAS_gut_mean, aes(x = reorder(dgrp_number, Ratio))): objet 'tab_GWAS_gut_mean' introuvableplot_ratio_DGRPError in eval(expr, envir, enclos): objet 'plot_ratio_DGRP' introuvablelist_lines = unique(tab_GWAS_gut$dgrp_id)
Tab = NULL
for(i in list_lines){
tmp= subset(tab_GWAS_gut,dgrp_id==i)
sample_size= tmp %>% group_by(diet)%>%summarize(n=n())
test= t.test(totallength~diet ,data=tmp)
Tab = rbind(Tab, c(i,test$parameter,test$statistic,test$p.value,test$estimate,sample_size[1,2],sample_size[2,2]))
}
colnames(Tab)=c("Line","df","t","Pvalue","Mean_HS","Mean_HY","Sample_size_HS","Sample_size_HY")
Tab = as.data.frame(Tab)%>%
mutate(Pvalue=as.numeric(Pvalue),
Mean_HS =as.numeric(Mean_HS),
Mean_HY =as.numeric(Mean_HY),
Difference = Mean_HY-Mean_HS )
Tab$Pv_adjust = p.adjust(Tab$Pvalue,method = "BH") # Here I control
length(which(Tab$Pv_adjust>0.05))
# 56 lines have no significant difference in size between diets
length(which(Tab$Pv_adjust<=0.05))
#132 lines have a significant difference in size between diets
Tab_sign = subset(Tab,Pv_adjust<=0.05)
length(which(Tab_sign$Difference<=0))
# 0 line was significantly smaller on HY
length(which(Tab_sign$Difference>0))
# 132 lines (i.e. all of those that were different) were significantly larger on HYMidgut re-sizing is allometric between regions of the midgut. Posterior midguts of flies fed HY exhibit a greater increase than anterior regions.
tab_GWAS_gut=
tab_GWAS_gut%>%
mutate(allometry=posteriorlength/anteriorlength)Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"tab_GWAS_gut_allometry_mean=
tab_GWAS_gut%>%
group_by(diet,dgrp_number)%>%
summarise(mean_allometry=mean(allometry,na.rm=T))Error in UseMethod("group_by"): pas de méthode pour 'group_by' applicable pour un objet de classe "NULL"Sample_size=
tab_GWAS_gut_allometry_mean%>%
group_by(diet)%>%
summarise(Sample_size=n())Error in group_by(., diet): objet 'tab_GWAS_gut_allometry_mean' introuvable###Stats
mod.gen = fitme(mean_allometry ~ diet + (1 | dgrp_number) , data = tab_GWAS_gut_allometry_mean)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_GWAS_gut_allometry_mean' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(mean_allometry ~ diet + (1 / dgrp_number) , data = tab_GWAS_gut_allometry_mean) Error in is.data.frame(data): objet 'tab_GWAS_gut_allometry_mean' introuvablemod.gen1 = fitme(mean_allometry ~ 1 + (1 | dgrp_number), data = tab_GWAS_gut_allometry_mean) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_GWAS_gut_allometry_mean' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = 1,
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in test$basicLRT: objet de type 'closure' non indiçabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("mean_allometry ~ diet + (1 | dgrp_number)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
Plot_Fig1G=
ggplot(tab_GWAS_gut_allometry_mean, aes(diet,mean_allometry, group=dgrp_number,color=diet)) +
geom_path(size=0.3,color=grey(0.65))+
geom_point(shape=16,size= 1)+
scale_x_discrete("",
expand=c(0.1,0.1),
limits=c("x","y"),
labels=c("HS", "HY"))+
scale_y_continuous("Posterior / anterior length",
limits=c(0.6, 1.4),
breaks=c(c(seq(0.5,1.4,by=0.1))))+
scale_color_manual(limits=c("x","y"),
values=palette_diet_2)+
annotate("text", label=paste("p=",tab_stat$Pvalue,sep=""), x= 1.5, y=1.4,size=3)+
stat_summary(fun = mean, aes(group = 1),geom = "point", colour = "black", fill = "yellow", size = 3, shape = 23) +
stat_summary(fun=mean, colour="black", geom="line", aes(group = 1),size=1,linetype=2)+
theme(
axis.title.x = element_text(size=Smallfont),
axis.title.y = element_text(size=Smallfont),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
legend.position = "none",
panel.background = element_blank())Error in ggplot(tab_GWAS_gut_allometry_mean, aes(diet, mean_allometry, : objet 'tab_GWAS_gut_allometry_mean' introuvablePlot_Fig1GError in eval(expr, envir, enclos): objet 'Plot_Fig1G' introuvable##Export Figure 1
Canton S (Cs) flies fed HS diet have narrower midguts than those fed HY diet. Width was measured in three point along the gut (Region 2, 3 and 4, as visible in the yellow annotation in Figure 1C,D) and the sum of these three measurement was used as proxy for midgut width. Measurements are from the same guts as in Figure 1E
Length_HSHY =
d[["1E - 1S1A"]]%>%
mutate_at(vars(starts_with("Total")),~./1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Total_Length_mm=Total.L,
Total_width_mm=Total.W,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_HSHY%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'Length_HSHY' introuvable###Stats
mod.gen = fitme(log(Total_width_mm) ~ Diet + (1 | Repeat), data = Length_HSHY)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_width_mm) ~ Diet + (1 / Repeat), data = Length_HSHY) Error in is.data.frame(data): objet 'Length_HSHY' introuvablemod.gen1 = fitme(log(Total_width_mm) ~ 1 + (1 | Repeat), data = Length_HSHY) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(Length_HSHY$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_HSHY' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_width_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
Limits = c("HS", "HY")
z = max(Length_HSHY$Total_width_mm)Error in eval(expr, envir, enclos): objet 'Length_HSHY' introuvablePlot_Fig1S1A=
ggplot(Length_HSHY, aes(x = Diet, y = Total_width_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.6) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/50) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 0.25, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 0.93, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS", "HY"),
breaks=c("HS", "HY"))+
scale_y_continuous("Midgut width (mm)",
limits=c(0.2,1),
breaks=seq(0.2,1,by=0.1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18,colour = "black",aes(group=Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18,aes(group=Repeat, colour = Repeat)) +
scale_color_manual(values=palette_mean)+
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(Length_HSHY, aes(x = Diet, y = Total_width_mm)): objet 'Length_HSHY' introuvablePlot_Fig1S1AError in eval(expr, envir, enclos): objet 'Plot_Fig1S1A' introuvableLength of midguts on HY diet is similar to standard diets used in the field (Bloomington [Bl] cornmeal and Bl molasses).
tab_stddiets_rev =
d[["1 - S1B"]]%>%
mutate(Total_Length_mm =Total.L/1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
mutate(Sugar=fct_relevel(Diet,"HS","HY", "BL Cornmeal", "BL Molasses"))Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"Sample_size=
tab_stddiets_rev%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_stddiets_rev' introuvable###Stats
mod.gen = fitme((Total_Length_mm) ~ Diet + (1 | Repeat), data = tab_stddiets_rev)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_stddiets_rev' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((Total_Length_mm) ~ Diet + (1 / Repeat), data = tab_stddiets_rev) Error in is.data.frame(data): objet 'tab_stddiets_rev' introuvablemod.gen1 = fitme((Total_Length_mm) ~ 1 + (1 | Repeat), data = tab_stddiets_rev) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_stddiets_rev' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("Anova diets")),
Rep = nlevels(tab_stddiets_rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_stddiets_rev' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("(Total_Length_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvablemod.gen = lmer(Total_Length_mm ~ Diet + (1 | Repeat), data = tab_stddiets_rev)Error: bad 'data': objet 'tab_stddiets_rev' introuvablemultcomp = glht(mod.gen, linfct=mcp(Diet="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=tab_stddiets_rev,Total_Length_mm ~ Diet, max)Error in eval(m$data, parent.frame()): objet 'tab_stddiets_rev' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Diet=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvableLimits =c("HS","HY", "BL Cornmeal", "BL Molasses")
Labels =c("HS","HY", "Bl cornmeal", "Bl molasses")
cbbPalette = c("#FFB4B4","#C3E6FC", "#f6efe5", "#f6efe5")
z = max(tab_stddiets_rev$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_stddiets_rev' introuvablePlot_Fig1S1B=
ggplot(tab_stddiets_rev, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8, alpha = 0.5) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/35) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.8, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 2.5, y = 7.5, label = paste("p=",format(Pvalue,digits=2))),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Total_Length_mm+0.6, label = Letter),size=3)+
scale_fill_manual(limits=Limits,
values=cbbPalette)+
scale_x_discrete("",
limits=Limits,
labels=Labels)+
scale_y_continuous("Midgut length (mm)",
limits=c(1.6,8),
breaks=seq(2,7,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_stddiets_rev, aes(x = Diet, y = Total_Length_mm)): objet 'tab_stddiets_rev' introuvablePlot_Fig1S1BError in eval(expr, envir, enclos): objet 'Plot_Fig1S1B' introuvableUn-mated females and mated males have lower response to diet compared to mated female flies. Statistics: comparison of the interaction between diet and mating status/sex. Full annotation on figure present in manuscript
tab_MUmM_rev =
d[["1 - S1C"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
mutate(Treatment=fct_relevel(Treatment,c("Mated females","Un-mated females","Males")))Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_MUmM_rev%>%
group_by(Diet,Treatment)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Treatment): objet 'tab_MUmM_rev' introuvable###Stats
#Un-mated
tmp = subset(tab_MUmM_rev, Treatment%in%c("Mated females","Un-mated females"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_MUmM_rev' introuvablemod.gen = fitme((Total_Length_mm) ~ Diet * Treatment + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((Total_Length_mm) ~ Diet + Treatment + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme((Total_Length_mm) ~ Diet + Treatment + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Treatment = as.character(paste("Mated vs Un-mated females")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Un_mated=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Male
tmp = subset(tab_MUmM_rev, Treatment%in%c("Mated females","Males"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_MUmM_rev' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet * Treatment + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Treatment + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Treatment + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Treatment = as.character(paste("Mated vs Males")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Male=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_Male,tab_stat_Un_mated)Error in eval(quote(list(...)), env): objet 'tab_stat_Male' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.009, "*", #changed to 0.009 because Un-mated is exactle 0.01
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.009, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Diet + Treatment + Diet : Treatment + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Variable", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat$Treatment = as.factor(tab_stat$Treatment)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_stat' introuvabletabError in eval(expr, envir, enclos): objet 'tab' introuvable### Plot
tab_stat_1S1C=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvablePlot_Fig1S1C=
ggplot(tab_MUmM_rev, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.15) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.7, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~ Treatment)+
scale_fill_manual(values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS","HY"),
labels=c("HS","HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(1.5,8),
breaks=seq(2,6,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_MUmM_rev, aes(x = Diet, y = Total_Length_mm)): objet 'tab_MUmM_rev' introuvablePlot_Fig1S1CError in eval(expr, envir, enclos): objet 'Plot_Fig1S1C' introuvableFeeding assay shows higher dietary intake on HS than on HY diet. Absorbance measured after 1 day of assay, each day along a 5-day period from eclosion, for a total of 5 times per condition/repeat
Tab_absorbance =
d[["1 - S1D"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Diet=Food)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Tab_absorbance%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'Tab_absorbance' introuvable###Stats
mod.gen = fitme(Absorbance ~ Diet + (1 | Repeat), data = Tab_absorbance)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_absorbance' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(Absorbance ~ Diet + (1 / Repeat), data = Tab_absorbance) Error in is.data.frame(data): objet 'Tab_absorbance' introuvablemod.gen1 = fitme(Absorbance ~ 1 + (1 | Repeat), data = Tab_absorbance) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_absorbance' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(Tab_absorbance$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_absorbance' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("Absorbance ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable##Plot
Limits = c("HS", "HY")
z = max(Tab_absorbance$Absorbance)Error in eval(expr, envir, enclos): objet 'Tab_absorbance' introuvablePlot_Fig1S1D=
ggplot(Tab_absorbance, aes(x = Diet, y = Absorbance))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 0.02, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 0.58, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS", "HY"),
breaks=c("HS", "HY"))+
scale_y_continuous("Absorbance",
limits=c(0,0.6),
breaks=seq(0,0.5,by=0.1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18,colour = "black",aes(group=Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18,aes(group=Repeat, colour = Repeat)) +
scale_color_manual(values=palette_mean)+
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(Tab_absorbance, aes(x = Diet, y = Absorbance)): objet 'Tab_absorbance' introuvablePlot_Fig1S1DError in eval(expr, envir, enclos): objet 'Plot_Fig1S1D' introuvableMicrobes are not required for the difference in size observed between HS and HY fed flies. Germ-free flies exhibit similar diet-induced increase in size as conventionally reared flies at both 7- and 14-days post eclosion (statistics: comparison of the interaction between diets and conv. reared/germ free treatment). Of note, at 7-days post eclosion we observed longer guts in germ free flies compared to conventionally reared flies (significant on HS diet). This difference was lost at 14-days post eclosion (Post hoc Tukey test from GLMM summarized by letter at the bottom of chart). Full statistical annotation on figure present in manuscript
Length_HSHY_germfree =
d[["1 - S1E"]]%>%
mutate_at(vars(starts_with("Total")),~./1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Total_Length_mm=Total.L,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_HSHY_germfree%>%
group_by(Diet,Treatment, Day_of_treatment)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Treatment, Day_of_treatment): objet 'Length_HSHY_germfree' introuvableSample_size$Sample_size <- as.numeric(Sample_size$Sample_size)Error in eval(expr, envir, enclos): objet 'Sample_size' introuvable###Stats Day 7 interaction
Length_HSHY_germfree_Day7 = subset(Length_HSHY_germfree, Day_of_treatment == "7")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_HSHY_germfree' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + Treatment + Diet : Treatment + (1 | Repeat), data = Length_HSHY_germfree_Day7)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY_germfree_Day7' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Treatment + (1 / Repeat), data = Length_HSHY_germfree_Day7) Error in is.data.frame(data): objet 'Length_HSHY_germfree_Day7' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Treatment + (1 | Repeat), data = Length_HSHY_germfree_Day7) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY_germfree_Day7' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat7 = data.frame(Variable = as.character(paste("Response to diet Day7")),
Rep = as.numeric(nlevels(Length_HSHY_germfree_Day7$Repeat)),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[4],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_HSHY_germfree_Day7' introuvabletab_stat7$sig = ifelse(tab_stat7$Pvalue < 0.05 & tab_stat7$Pvalue > 0.01, "*",
ifelse(tab_stat7$Pvalue < 0.01 & tab_stat7$Pvalue > 0.001, "**",
ifelse(tab_stat7$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat7$Pvalue < 0.05 & tab_stat7$Pvalue > 0.01, "*", : objet 'tab_stat7' introuvabletab_stat7%>%
kable(col.names = c("Response to diet Day7", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + Treatment + Diet : Treatment + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Response to diet Day7", "Replicates", : objet 'tab_stat7' introuvabletab_stat_int_GF7=tab_stat7Error in eval(expr, envir, enclos): objet 'tab_stat7' introuvable###Stats Day 14 interaction
Length_HSHY_germfree_Day14 = subset(Length_HSHY_germfree, Day_of_treatment == "14")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_HSHY_germfree' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + Treatment + Diet : Treatment + (1 | Repeat), data = Length_HSHY_germfree_Day14)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY_germfree_Day14' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Treatment + (1 / Repeat), data = Length_HSHY_germfree_Day14) Error in is.data.frame(data): objet 'Length_HSHY_germfree_Day14' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Treatment + (1 | Repeat), data = Length_HSHY_germfree_Day14) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_HSHY_germfree_Day14' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat14 = data.frame(Variable = as.character(paste("Response to diet Day14")),
Rep = as.numeric(nlevels(Length_HSHY_germfree_Day14$Repeat)),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[4],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_HSHY_germfree_Day14' introuvabletab_stat14$sig = ifelse(tab_stat14$Pvalue < 0.05 & tab_stat14$Pvalue > 0.01, "*",
ifelse(tab_stat14$Pvalue < 0.01 & tab_stat14$Pvalue > 0.001, "**",
ifelse(tab_stat14$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat14$Pvalue < 0.05 & tab_stat14$Pvalue > 0.01, "*", : objet 'tab_stat14' introuvabletab_stat14%>%
kable(col.names = c("Response to diet Day14", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + Treatment + Diet : Treatment + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Response to diet Day14", "Replicates", : objet 'tab_stat14' introuvabletab_stat_int_GF14=tab_stat14Error in eval(expr, envir, enclos): objet 'tab_stat14' introuvable#Model including all samples and Post HOC test
Length_HSHY_germfree$Treat_Diet_Day = as.factor(paste(Length_HSHY_germfree$Treatment, Length_HSHY_germfree$Diet, Length_HSHY_germfree$Day_of_treatment, sep="_"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'Length_HSHY_germfree' introuvablemod.gen = lmer(log(Total_Length_mm) ~ Treat_Diet_Day + (1 | Repeat), data = Length_HSHY_germfree)Error: bad 'data': objet 'Length_HSHY_germfree' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Treat_Diet_Day + (1/ Repeat), data = Length_HSHY_germfree)Error in is.data.frame(data): objet 'Length_HSHY_germfree' introuvablemultcomp = glht(mod.gen, linfct=mcp(Treat_Diet_Day="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=Length_HSHY_germfree,Total_Length_mm ~ Treat_Diet_Day, min)Error in eval(m$data, parent.frame()): objet 'Length_HSHY_germfree' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Treat_Diet_Day=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvabletab_letter$Treat_Diet_Day= as.factor(tab_letter$Treat_Diet_Day)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_letter' introuvabletab_letter$Day_of_treatment = as.factor(mid(tab_letter$Treat_Diet_Day,7, 2))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'substr' : objet 'tab_letter' introuvabletab_letter$Diet = as.factor(mid(tab_letter$Treat_Diet_Day, 4,2))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'substr' : objet 'tab_letter' introuvabletab_letter$Treatment = as.factor(left(tab_letter$Treat_Diet_Day, 2))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'substr' : objet 'tab_letter' introuvable### Plot
Limits = c("HS", "HY")
z= max(Length_HSHY_germfree$Total_Length_mm)Error in eval(expr, envir, enclos): objet 'Length_HSHY_germfree' introuvableTreatment.status = c("Conv. reared", "Germ free")
names(Treatment.status) = c("CR", "GF")
Plot_Fig1S1E=
ggplot(Length_HSHY_germfree, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/50) +
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Total_Length_mm-0.4, label = Letter),size=3)+
facet_wrap(Day_of_treatment~Treatment,labeller=labeller(Treatment=Treatment.status), nrow = 1)+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.35, label = paste("(",Sample_size,")",sep="")),size=3)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS", "HY"),
breaks=c("HS", "HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(1,8),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18,colour = "black",aes(group=Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18,aes(group=Repeat, colour = Repeat)) +
stat_summary(fun=mean, colour="black", geom="line",aes(group=Repeat))+
scale_color_manual(values=palette_mean)+
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size =Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_HSHY_germfree, aes(x = Diet, y = Total_Length_mm)): objet 'Length_HSHY_germfree' introuvablePlot_Fig1S1EError in eval(expr, envir, enclos): objet 'Plot_Fig1S1E' introuvable##Export Figure S1
Scheme depicting regional organization of the gut. The gut comprises three main anatomical regions: foregut (comprising the crop), midgut and hindgut. The midgut itself can be divided in anterior (blue), middle (green) and posterior (purple). Additional subregions have been described (Buchon et al., 2013; Marianes and Spradling, 2013).
img1S2A = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/1- S2A.jpg") Error in transpose(y): object is NULL gob_imageFig1S2A = rasterGrob(img1S2A)Error in rasterGrob(img1S2A): objet 'img1S2A' introuvable grid.draw(gob_imageFig1S2A)Error in grid.draw(gob_imageFig1S2A): objet 'gob_imageFig1S2A' introuvableAll regions of the midgut (x-axis) respond variably to diet composition, but the response of the posterior midgut length more closely reflects the response of the total midgut length. Red lines represent linear regression and black dashed lines are the lines of equivalence.
tab_GWAS_gut$dgrpDiet = factor(paste(tab_GWAS_gut$dgrp_id, tab_GWAS_gut$diet), ordered=T)
meansMat = aggregate(as.matrix(tab_GWAS_gut[,c("anteriorlength", "middlelength", "posteriorlength", "totallength")]) ~ diet * dgrp_id, tab_GWAS_gut, mean)
rownames(meansMat) = paste(meansMat$dgrp_id, meansMat$diet, sep="_")
colnames(meansMat) <- c("diet","dgrp_id", "Anterior Length", "Middle Length", "Posterior Length", "Total Length")
meansMatX = subset(meansMat, diet=="x")
meansMatY = subset(meansMat, diet=="y")
all(meansMatX$dgrp_id == meansMatY$dgrp_id)
meansMatX = meansMatX[,!colnames(meansMatX) %in% c("dgrp_id", "diet")]
meansMatY = meansMatY[,!colnames(meansMatY) %in% c("dgrp_id", "diet")]
meansMatY=
meansMatY %>%
setNames(str_to_sentence(names(.)))
meansMatX=
meansMatX %>%
setNames(str_to_sentence(names(.)))
RIs <- meansMatY / meansMatX
RIs <- RIs[,!grepl("width", colnames(RIs))]
plotRegress <- function(x,y, datRange, textCex, ...){
regn <- lm(y ~ x)
plot(y ~ x, xlim=datRange, ylim=datRange, ...)
abline(a=0,b=1, col=alpha(1, 0.5), lty=2)
abline(a=coef(regn)[1], b=coef(regn)[2],col=2)
val=round(summary(regn)$adj.r.squared, 1)
text(y=max(datRange), x=min(datRange),
labels=bquote(R^2 ~"="~ .(val)), adj=0, cex=textCex)
text(y=max(datRange) - (0.1 * diff(range(RIs))), x=min(datRange),
labels=paste("p =", signif(summary(regn)$coefficients[2,4], 2)), adj=0, cex=textCex)
text(y=max(datRange) - (0.2 * diff(range(RIs))), x=min(datRange),
labels=paste("y = ", signif(coef(regn)[2], 2), "x", " + ", signif(coef(regn)[1], 2), sep=""), adj=0, cex=textCex)
}
jpeg(filename = "Plot_Fig1S2B.jpeg",
res = 300,
width = 9, height = 3, units = 'in' )
par(bty="n", mfrow=c(1,3), cex.main=1.4, cex.lab=1.4, cex.axis=1.4)
for(i in 1:3){
plotRegress(x=RIs[,i], y=RIs[,4], xlab=paste(c("Anterior", "Middle", "Posterior")[i], "HY length / HS length"), ylab="Total HY length / HS length", bty="n", cex=0.75, pch=16, datRange=range(RIs), las=1, asp =1, textCex=1.4)
}
dev.off() img1S2B = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig1S2B.jpeg") Error in transpose(y): object is NULL gob_imageFig1S2B = rasterGrob(img1S2B)Error in rasterGrob(img1S2B): objet 'img1S2B' introuvable grid.draw(gob_imageFig1S2B)Error in grid.draw(gob_imageFig1S2B): objet 'gob_imageFig1S2B' introuvable##Export Figure 1S2
Variation in impact of diet on midgut length in the DGRP maps to genes with functions connected to epithelial turnover. The Manhattan plot summarizes the p-value per chromosomal locus (grey bars) associated with GWAS analysis. Highlighted genes have been selected based on their statistical significance, their function, and the effect of the genetic variation (e.g. non-synonymous mutation, etc.).
img1S3A = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/1 - S3.jpg") Error in transpose(y): object is NULLgob_imageFig1S3A = rasterGrob(img1S3A)Error in rasterGrob(img1S3A): objet 'img1S3A' introuvablegrid.draw(gob_imageFig1S3A)Error in grid.draw(gob_imageFig1S3A): objet 'gob_imageFig1S3A' introuvable##Export Figure
Midgut length is maximized at specific points in diet space. Adult flies were maintained for 5 days from eclosion on one of 28 diets based on different caloric concentration and yeast to sucrose ratios (see figure 1-figure supplement 1A for scheme on diets used and sample size). The list of recipes can be found in Table1. The figure shows contours of a thin-plate spline (Generalized Additive Model) of length (mm, coded by colors) as a function of yeast and sucrose in diet. Colored dots represent mean of samples in a particular diet.
tab_nutri_geo =
d[["2A"]]%>%
mutate(Total.Lmm = Total.L / 1000)
tab_nutri_geo$YSdiet <- with(tab_nutri_geo, (Yeast.in.Diet)/(Sucrose.in.Diet))
tab_nutri_geo$YSingested <- with(tab_nutri_geo, (Yeast.ingested)/(Sucrose.ingested))
jpeg(filename = "F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig2A.jpeg",
res = 600,
width = 5, height = 4, units = 'in' )
par(cex=1, mar = c(4.5, 4.5, 1, 3))
with(tab_nutri_geo, geomPlotta(x = Sucrose.in.Diet, y = Yeast.in.Diet, z = Total.Lmm, alf = 1, xlim = c(-10, 300), ylim = c(-10, 300), xlab = "Sucrose in diet (g/L)", ylab = "Yeast in diet (g/L)", frame.plot= FALSE, cex.lab=1.2, cex.axis =1, las=1, labcex=1, asp=1))img2A = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig2A.jpeg")Error in transpose(y): object is NULLgob_imageFig2A = rasterGrob(img2A)Error in rasterGrob(img2A): objet 'img2A' introuvablegrid.draw(gob_imageFig2A)Error in grid.draw(gob_imageFig2A): objet 'gob_imageFig2A' introuvablePlot show an increase in midgut length with increased amount of yeast ingested.
tab_nutri_geo =
d[["2A"]]%>%
mutate(Total.Lmm = Total.L / 1000)Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"tab_nutri_geo$title1 <- "Midgut length vs yeast ingested"Error in tab_nutri_geo$title1 <- "Midgut length vs yeast ingested": objet 'tab_nutri_geo' introuvablegraph2 <- ggplot(tab_nutri_geo, aes(x=Yeast.ingested, y=Total.Lmm))Error in ggplot(tab_nutri_geo, aes(x = Yeast.ingested, y = Total.Lmm)): objet 'tab_nutri_geo' introuvablePlot_Fig2B=
graph2 + geom_point(size=2,shape=16) + geom_smooth(span=1, size=1, color = "blue") +
scale_y_continuous("Midgut length (mm)") +
scale_x_continuous("Yeast ingested (g/L x absorbance)") +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"))Error in eval(expr, envir, enclos): objet 'graph2' introuvablePlot_Fig2BError in eval(expr, envir, enclos): objet 'Plot_Fig2B' introuvablePlots show a decrease in midgut length with increased amount of sucrose ingested.
tab_nutri_geo =
d[["2A"]]%>%
mutate(Total.Lmm = Total.L / 1000)Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"graph3 <- ggplot(tab_nutri_geo, aes(x=Sucrose.ingested, y=Total.Lmm))Error in ggplot(tab_nutri_geo, aes(x = Sucrose.ingested, y = Total.Lmm)): objet 'tab_nutri_geo' introuvablePlot_Fig2C=
graph3 + geom_point(size=2,shape=16) + geom_smooth(span=1, size=1, color = "red")+
scale_y_continuous("Midgut length (mm)") +
scale_x_continuous("Sucrose ingested (g/L x absorbance)") +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"))Error in eval(expr, envir, enclos): objet 'graph3' introuvablePlot_Fig2CError in eval(expr, envir, enclos): objet 'Plot_Fig2C' introuvablePlot show an increase in midgut length with ratio of yeast to sucrose ingested.
tab_nutri_geo =
d[["2A"]]%>%
mutate(Total.Lmm = Total.L / 1000)Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"graph4 <- ggplot(tab_nutri_geo, aes(x=(Yeast.ingested/Sucrose.ingested), y=Total.Lmm))Error in ggplot(tab_nutri_geo, aes(x = (Yeast.ingested/Sucrose.ingested), : objet 'tab_nutri_geo' introuvablePlot_Fig2D=
graph4 + geom_point(size=2,shape=16) + geom_smooth(span=1, size=1, color = "green")+
scale_y_continuous("Midgut length (mm)") +
scale_x_continuous("Y:S ingested") +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"))Error in eval(expr, envir, enclos): objet 'graph4' introuvablePlot_Fig2DError in eval(expr, envir, enclos): objet 'Plot_Fig2D' introuvableSeveral nutrients from yeast (proteins, lipids, vitamins/minerals) are required to increase midgut length. Nutrients from yeast (proteins, amino acids, lipids, cholesterol, vitamins/minerals) were added against a base diet of only the amount of sucrose found in HY and devoid of yeast. Letters above violin plots represent grouping by statistical differences (Post hoc Tukey on GLMM). Bars beneath the main plot describe caloric content provided by the different components. Proper label annotation (in line with the chart) can be found in manuscript figures
tab_lenght_complement =
d[["2E"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Diet=Food,
Total_Length_mm = Total.Lmm)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"tab_lenght_complement$Diet = factor(tab_lenght_complement$Diet, levels = c("HS",
"S74Y0 (A)",
"A+Cas2",
"A+Cas4",
"A+AA",
"A+AA2",
"A+L4",
"A+Ch0.4",
"A+L2+Ch0.2",
"A+L4+Ch0.4",
"A+V2",
"A+V4",
"A+C4+L4+Ch0.4",
"A+C4+L4+Ch0.4+V2",
"HY")) #Order DietsError in factor(tab_lenght_complement$Diet, levels = c("HS", "S74Y0 (A)", : objet 'tab_lenght_complement' introuvableSample_size=
tab_lenght_complement%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_lenght_complement' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tab_lenght_complement)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_lenght_complement' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tab_lenght_complement) Error in is.data.frame(data): objet 'tab_lenght_complement' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tab_lenght_complement) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_lenght_complement' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("Anova diets")),
Rep = nlevels(tab_lenght_complement$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lenght_complement' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvablemod.gen = lmer(Total_Length_mm ~ Diet + (1 | Repeat), data = tab_lenght_complement)Error: bad 'data': objet 'tab_lenght_complement' introuvablemultcomp = glht(mod.gen, linfct=mcp(Diet="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=tab_lenght_complement,Total_Length_mm ~ Diet, max)Error in eval(m$data, parent.frame()): objet 'tab_lenght_complement' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Diet=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvable### Plot
Limits= c("HS", "S74Y0 (A)", "A+Cas2", "A+Cas4", "A+AA", "A+AA2", "A+L4", "A+Ch0.4", "A+L2+Ch0.2", "A+L4+Ch0.4", "A+V2", "A+V4", "A+C4+L4+Ch0.4","A+C4+L4+Ch0.4+V2", "HY")
cbbPalette = c("#FFB4B4", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#C3E6FC")
z = max(tab_lenght_complement$Total_Length_mm, na.rm=TRUE)Error in eval(expr, envir, enclos): objet 'tab_lenght_complement' introuvablePlot_Fig2E=
ggplot(tab_lenght_complement, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z / 60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.2, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Total_Length_mm+0.4, label = Letter),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 2, y = 7.5, label = paste("p=",Pvalue)),size=3)+
scale_fill_manual(limits=Limits,
values=cbbPalette)+
scale_x_discrete("",
limits=Limits)+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8),
breaks=seq(3,7,by=1))+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 1, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_blank(),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.5, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_lenght_complement, aes(x = Diet, y = Total_Length_mm)): objet 'tab_lenght_complement' introuvabletab_component_calories= mutate_if(d[["2E - calories"]],is.character,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"tab_component_calories$Component <- factor(tab_component_calories$Component, levels = c("Lipids", "Proteins", "Carbohydrates"))Error in factor(tab_component_calories$Component, levels = c("Lipids", : objet 'tab_component_calories' introuvableLimits_2 = c("Lipids","Proteins","Carbohydrates")
Labels = c("Lipids","Proteins","Carbohydrates")
Plot_Fig2E_bis=
ggplot(tab_component_calories,aes(x=Diet,y=Calories.contributed))+
geom_bar(stat="identity",aes(fill=Component),color="black",width=.90)+
scale_fill_manual(limits=Limits_2,
values=palette_component_3,
labels=Labels)+
scale_x_discrete("",
limits=Limits)+
scale_y_reverse("Calories",
breaks=c(seq(0,1400,by=300)))+
theme(axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="white"),
axis.line.y = element_line(colour="black"),
axis.ticks.x = element_line(colour="white"),
axis.ticks.y = element_line(),
axis.text.x = element_blank(),
axis.text.y = element_text(size=Smallfont,colour="black"),
panel.grid = element_blank(),
plot.margin = unit(c(0,0,0,0), "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = "bottom",
legend.margin=margin(t=0.1, r=0.2, b=0.1, l=0, unit="cm"),
legend.title = element_blank(),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill="white", colour="black"),
legend.key.size = unit(0.5,"cm"),
strip.text.x = element_text(size =Mediumfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Mediumfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside",
panel.background = element_rect(fill="transparent"))+
guides(fill=guide_legend(ncol=3))Error in ggplot(tab_component_calories, aes(x = Diet, y = Calories.contributed)): objet 'tab_component_calories' introuvableplot_2E = grid.arrange(Plot_Fig2E,
Plot_Fig2E_bis+ theme(legend.position="none"),
grid.text("HS",x=0.15, y=0.2, just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
grid.text("HY",x=0.95, y=1, just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
grid.text("Sucrose in HY completed with:",x=0.21, y=0.9,just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
grid.text("Casein x0 x2 x4 x4 x4", x=0.02, y=0.52,just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
grid.text("AAs x0 x1 x2", x=0.02, y=0.51,just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
grid.text("Lard x0 x4 x2 x4 x4 x4", x=0.02, y=0.50,just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
grid.text("Chol. x0 x1 x1 x1 x1 x1", x=0.02, y=0.49,just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
grid.text("Vit. x0 x2 x4 x2", x=0.02, y=0.48,just="left",gp = gpar(fontsize=Smallfont,fontface="bold")),
ncol = 1, heights = c(2,1,0.2,0.15, 0.15,0.15,0.15,0.15,0.15,0.2))Error in arrangeGrob(...): objet 'Plot_Fig2E' introuvableMidgut size is antagonized by sugar, but not other added calories. Diet with only lipids, isocaloric with HS and HY diets, results in midguts of lengths comparable to those on HS diet. Substitution of sucrose from HS diet with isocaloric lipids (Lipids HS) results in midguts as long as those on HY. Midguts of flies reared on a diet substituting sucrose in HY diet with lipids (Lipids HY) are also similar in length to those of flies fed HY. Letters above violin plots represent grouping by statistical differences (Post hoc Tukey on GLMM). Bottom part of the chart (bar graph) describes caloric content provided by the different components.
tab_lipids =
d[["2F"]]%>%
mutate(Total_Length_mm =Total.L/1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Diet=Food)Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"Sample_size=
tab_lipids%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_lipids' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tab_lipids)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_lipids' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tab_lipids) Error in is.data.frame(data): objet 'tab_lipids' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tab_lipids) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_lipids' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("Anova diets")),
Rep = nlevels(tab_lipids$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lipids' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvablemod.gen = lmer(Total_Length_mm ~ Diet + (1 | Repeat), data = tab_lipids)Error: bad 'data': objet 'tab_lipids' introuvablemultcomp = glht(mod.gen, linfct=mcp(Diet="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=tab_lipids,Total_Length_mm ~ Diet, max)Error in eval(m$data, parent.frame()): objet 'tab_lipids' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Diet=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvableLimits =c("Lard Only","HS","HS Lard sub","HY Lard sub","HY")
Labels =c("Yeast:Lipid 0:1","Yeast:Sugar 1:14 (HS)","Yeast:Lipid 1:14","Yeast:Lipid 1:0.7","Yeast:Sugar 1:0.7 (HY)")
cbbPalette = c("#f6efe5", "#FFB4B4", "#f6efe5", "#f6efe5", "#C3E6FC")
z = max(tab_lipids$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_lipids' introuvablePlot_Fig2F=
ggplot(tab_lipids, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8, alpha = 0.5) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 1.7, y = 7.5, label = paste("p=",format(Pvalue,digits=2))),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Total_Length_mm+0.4, label = Letter),size=3)+
scale_fill_manual(limits=Limits,
values=cbbPalette)+
scale_x_discrete("",
limits=Limits,
labels=Labels)+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8.2),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_blank(),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_lipids, aes(x = Diet, y = Total_Length_mm)): objet 'tab_lipids' introuvabletab_component_calories_2F= mutate_if(d[["2F - calories"]],is.character,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Limits_1 =c("Lard Only","HS","HS Lard","HY Lard","HY")
Labels_1 =c("Yeast:Lipid 0:1","Yeast:Sugar 1:14 (HS)","Yeast:Lipid 1:14","Yeast:Lipid 1:0.7","Yeast:Sugar 1:0.7 (HY)")
tab_component_calories_2F$Component <- factor(tab_component_calories_2F$Component, levels = c("Lipids", "Proteins", "Carbohydrates"))Error in factor(tab_component_calories_2F$Component, levels = c("Lipids", : objet 'tab_component_calories_2F' introuvableLimits_2 = c("Lipids","Proteins","Carbohydrates")
Labels_2 = c("Lipids","Proteins","Carbohydrates")
Plot_Fig2F_bis=
ggplot(tab_component_calories_2F,aes(x=Diet,y=Calories.contributed))+
geom_bar(stat="identity",aes(fill=Component),color="black",width=.90)+
scale_x_discrete("",
limits=Limits_1,
labels=Labels_1)+
scale_y_reverse("Calories",
breaks=c(seq(0,600,by=200)))+
scale_fill_manual(limits=Limits_2,
values=palette_component_3,
labels=Labels_2)+
theme(axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="white"),
axis.line.y = element_line(colour="black"),
axis.ticks.x = element_line(colour="white"),
axis.ticks.y = element_line(),
axis.text.x = element_text(size=Smallfont,colour="black",angle=45,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
panel.grid = element_blank(),
plot.margin = unit(c(0,0,0,0), "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = "bottom",
legend.key.height = unit(0.3, "cm"),
legend.key.width= unit(0.3, "cm"),
legend.margin=margin(t=0, r=0, b=0, l=0, unit="cm"),
legend.title = element_blank(),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Mediumfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Mediumfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside",
panel.background = element_rect(fill="transparent"))+
guides(fill=guide_legend(ncol=3))Error in ggplot(tab_component_calories_2F, aes(x = Diet, y = Calories.contributed)): objet 'tab_component_calories_2F' introuvableg_legend=function(a.gplot){
tmp = ggplot_gtable(ggplot_build(a.gplot))
leg = which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend = tmp$grobs[[leg]]
return(legend)}
mylegend=g_legend(Plot_Fig2F_bis)Error in ggplot_build(a.gplot): objet 'Plot_Fig2F_bis' introuvableplot_2F = grid.arrange(Plot_Fig2F,
Plot_Fig2F_bis+ theme(legend.position="none"),
ncol = 1, heights = c(2,2))Error in arrangeGrob(...): objet 'Plot_Fig2F' introuvableAntagonism by sugar of yeast-induced growth is not specific to sucrose. Statistical comparisons were performed with HS vs HY for each sugar.
tab_sugars =
d[["2G"]]%>%
mutate(Total_Length_mm =Total.L/1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Day_of_Treatment=Day)Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"tab_sugars$Sugar = factor(c("Sucrose","Fructose","Glucose","Maltose"), levels = c("Sucrose", "Glucose", "Fructose", "Maltose"))Error in tab_sugars$Sugar = factor(c("Sucrose", "Fructose", "Glucose", : objet 'tab_sugars' introuvableSample_size=
tab_sugars%>%
group_by(Diet,Sugar)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Sugar): objet 'tab_sugars' introuvable###Stats
# Sucrose:
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = subset(tab_sugars,Sugar=="Sucrose"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = subset(tab_sugars,Sugar=="Sucrose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = subset(tab_sugars,Sugar=="Sucrose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY sucrose")),
Rep = nlevels(tab_lipids$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lipids' introuvabletab_stat_sucrose =tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Glucose:
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = subset(tab_sugars,Sugar=="Glucose"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = subset(tab_sugars,Sugar=="Glucose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = subset(tab_sugars,Sugar=="Glucose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY glucose")),
Rep = nlevels(tab_lipids$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lipids' introuvabletab_stat_Glucose=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Fructose:
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = subset(tab_sugars,Sugar=="Fructose"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = subset(tab_sugars,Sugar=="Fructose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = subset(tab_sugars,Sugar=="Fructose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY fructose")),
Rep = nlevels(tab_lipids$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lipids' introuvabletab_stat_Fructose = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Maltose:
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = subset(tab_sugars,Sugar=="Maltose"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = subset(tab_sugars,Sugar=="Maltose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = subset(tab_sugars,Sugar=="Maltose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_sugars' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY maltose")),
Rep = nlevels(tab_lipids$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lipids' introuvabletab_stat_Maltose= tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat = rbind(tab_stat_sucrose,tab_stat_Glucose,tab_stat_Fructose,tab_stat_Maltose)Error in eval(quote(list(...)), env): objet 'tab_stat_sucrose' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat$Sugar = c("Sucrose","Glucose","Fructose","Maltose")Error in tab_stat$Sugar = c("Sucrose", "Glucose", "Fructose", "Maltose"): objet 'tab_stat' introuvabletab_stat$Sugar =as.factor(tab_stat$Sugar)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif.","Sugar"),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvableLimits = c("HS","HY")
Labels= c("HS","HY")
z = max(tab_sugars$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_sugars' introuvablePlot_Fig2G=
ggplot(tab_sugars, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot(colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z / 60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat,aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 8.5), textsize = 3, vjust = -0.2, manual = TRUE)+
facet_grid(.~Sugar)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=Limits,
labels=Labels)+
scale_y_continuous("Midgut length (mm)",
limits=c(2,9),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_sugars, aes(x = Diet, y = Total_Length_mm)): objet 'tab_sugars' introuvablePlot_Fig2GError in eval(expr, envir, enclos): objet 'Plot_Fig2G' introuvable##Export Figure 2
Set of diets utilized for the nutritional geometry experiment. Numbers on dots denote sample sizes for figure 2A (pool of three independent biological replicates). We utilized 28 different diets, varying either caloric content or the yeast to sucrose ratio. The complete list of recipes can be found in Table 1. Complete numbers can be found in manuscript figure
tab_nutri_geo_design =
d[["2 - S1A"]]%>%
dplyr::rename(Yeast.in.Diet=Yeast,
Sucrose.in.Diet=Sugar)Error in UseMethod("rename"): pas de méthode pour 'rename' applicable pour un objet de classe "NULL"tab_raw_2A =
d[["2A"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
mutate(Conc = paste(round(Sucrose.in.Diet,digits=2),"x",round(Yeast.in.Diet,digits=2),sep=""))%>%
group_by(Yeast.in.Diet,Sucrose.in.Diet)%>%
summarise(Sample_size=n())Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"tab_nutri_geo_design = left_join(tab_nutri_geo_design,tab_raw_2A)Error in left_join(tab_nutri_geo_design, tab_raw_2A): objet 'tab_nutri_geo_design' introuvablePlot_Fig2S1A=
ggplot(tab_nutri_geo_design, aes(x = Sucrose.in.Diet, y = Yeast.in.Diet,label=Sample_size))+
geom_point(aes(size=Calories), colour = "black") +
scale_x_continuous("Sucrose in diet (g/L)",
limits=c(-5,300),
breaks=seq(0,300,by=100))+
scale_y_continuous("Yeast in diet (g/L)",
limits=c(-5,300),
breaks=seq(0,300,by=100))+
geom_text(data=subset(tab_nutri_geo_design,Yeast.in.Diet>=30 | Sucrose.in.Diet>=30),color="white",size=3)+
scale_size_continuous(range = c(1,13)) +
theme(panel.background = element_blank(),
panel.grid.major = element_line(colour = "black",linetype=3),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = "top",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")+
guides(size=guide_legend(ncol=4))Error in ggplot(tab_nutri_geo_design, aes(x = Sucrose.in.Diet, y = Yeast.in.Diet, : objet 'tab_nutri_geo_design' introuvablePlot_Fig2S1AError in eval(expr, envir, enclos): objet 'Plot_Fig2S1A' introuvableHS and HY diet compared to standard diets used for Drosophila
FD&C1 blue transit assay (feeding assay) showing amount of food defecated, and by inference ingested, in the nutritional geometry experiment. The scale maps color to units. The graph indicates compensatory feeding at lower nutrient densities, especially low yeast. These data were used to calculate the total amount of yeast and sucrose ingested on each diet in Figure 2-supplemental figure 1C.
tab_geom_fecal =
d[["2 - S1B"]]
jpeg(filename = "F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig2-S1B.jpeg",
res = 600,
width = 5, height = 4, units = 'in' )
par(cex=1, mar = c(4, 4, 1, 3))
with(tab_geom_fecal, geomPlotta(x = Sucrose.in.Diet, y = Yeast.in.Diet, z = (Absorbance*10), alf = 1, xlim = c(-10, 300), ylim = c(-10, 300), xlab = "Sucrose in diet (g/L)", ylab = "Yeast in diet (g/L)", frame.plot= FALSE, cex.lab=1, cex.axis =1, las=1, labcex=1, asp=1))img2S1B = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig2-S1B.jpeg") Error in transpose(y): object is NULLgob_imageFig2S1B = rasterGrob(img2S1B)Error in rasterGrob(img2S1B): objet 'img2S1B' introuvablegrid.draw(gob_imageFig2S1B)Error in grid.draw(gob_imageFig2S1B): objet 'gob_imageFig2S1B' introuvableYeast and sucrose have mutually antagonistic impacts on midgut length. Plots show midgut length as a function of sucrose or yeast ingested (g/L x Absorbance from Figure 2-supplemental figure 1B), or their ratio multiplied by ingestion per diet.
tab_nutri_geo =
d[["2A"]]%>%
mutate(Total.Lmm = Total.L / 1000)Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"tab_nutri_geo2 <- tab_nutri_geo %>%
group_by(concatenate) %>%
summarize(Calories.ingested = mean(Calories.ingested),
Midgut.length = mean(Total.Lmm),
Yeast.ingested = mean(Yeast.ingested),
Sucrose.ingested = mean(Sucrose.ingested))Error in group_by(., concatenate): objet 'tab_nutri_geo' introuvablegraph <- ggplot(tab_nutri_geo2, aes(x=Sucrose.ingested, y=Yeast.ingested))Error in ggplot(tab_nutri_geo2, aes(x = Sucrose.ingested, y = Yeast.ingested)): objet 'tab_nutri_geo2' introuvablePlot_Fig2S1C=
graph + geom_point(aes(size=Calories.ingested, fill=Midgut.length), stroke=1.5, shape=21, color="black") +
scale_size(range = c(1,5)) +
scale_fill_viridis_c() +
theme(plot.title= element_text(hjust = 0.5))+
scale_x_continuous("Sucrose ingested (g/L x Absorbance)",
limits=c(-5,160),
breaks=seq(0,160,by=25))+
scale_y_continuous("Yeast ingested (g/L x Absorbance)",
limits=c(-5,50),
breaks=seq(0,50,by=10))+
scale_size_continuous(range = c(1,10)) +
theme(panel.background = element_blank(),
panel.grid.major = element_line(colour = "black",linetype=3),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "horizontal",
legend.box = "vertical",
legend.position = c(0.79,0.79),
legend.key.height = unit(0.3, "cm"),
legend.key.width= unit(0.4, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")+
labs(fill = "Midgut length (mm)", size = "Calories ingested")Error in eval(expr, envir, enclos): objet 'graph' introuvablePlot_Fig2S1CError in eval(expr, envir, enclos): objet 'Plot_Fig2S1C' introuvable##Export Figure 2S1
Food texture does not explain the differential effects of HS and HY diets on midgut length. Addition of inulin (inu), pectin (pect), cellulose (cell), and all previous fibers mixed (AF) or pectin + cellulose (PC) to HS does not increase midgut length. Addition of fibers to HY (HY + AF) and HY + pectin + cellulose (HY + PC2) does not affect midgut length.
tab_fiber =
d[["2 - S2A"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
mutate(Total_Length_mm = Total.L/1000)%>%
dplyr::rename(Diet=Food)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"tab_fiber$Diet = factor(tab_fiber$Diet, levels = c("HS", "HS + Inu", "HS + Pect", "HS + Pect2", "HS + Cell", "HS + Cell2", "HS + AF", "HS + PC2", "HY + AF", "HY + PC2", "HY")) Error in factor(tab_fiber$Diet, levels = c("HS", "HS + Inu", "HS + Pect", : objet 'tab_fiber' introuvableSample_size=
tab_fiber%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_fiber' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tab_fiber)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_fiber' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tab_fiber) Error in is.data.frame(data): objet 'tab_fiber' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tab_fiber) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_fiber' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("Any difference")),
Rep = nlevels(tab_fiber$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_fiber' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvablemod.gen = lmer(Total_Length_mm ~ Diet + (1 | Repeat), data = tab_fiber)Error: bad 'data': objet 'tab_fiber' introuvablemultcomp = glht(mod.gen, linfct=mcp(Diet="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=subset(tab_fiber,!is.na(Total_Length_mm)),Total_Length_mm ~ Diet, max)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_fiber' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Diet=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvable### Plot
Limits= c("HS", "HS + Inu", "HS + Pect", "HS + Pect2", "HS + Cell", "HS + Cell2", "HS + AF", "HS + PC2", "HY + AF", "HY + PC2", "HY")
cbbPalette = c("#FFB4B4", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5", "#f6efe5","#f6efe5", "#f6efe5", "#f6efe5", "#C3E6FC")
z = max(tab_fiber$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_fiber' introuvablePlot_Fig2S2A=
ggplot(tab_fiber, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Total_Length_mm+0.4, label = Letter),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 1.5, y = 7.5, label = paste("p=",format(Pvalue,digits=2))),size=3)+
scale_fill_manual(limits=Limits,
values=cbbPalette)+
scale_x_discrete("",
limits=Limits)+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=45,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_fiber, aes(x = Diet, y = Total_Length_mm)): objet 'tab_fiber' introuvablePlot_Fig2S2AError in eval(expr, envir, enclos): objet 'Plot_Fig2S2A' introuvableChanges in food texture due to variation in agar concentration can affect midgut length but do not explain the effect of the diet treatment. Changes in agar concentration do not change midgut length on HS. Either increasing or decreasing agar concentration reduces midgut length on HY.
tab_agar =
d[["2 - S2B"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
mutate(Total_Length_mm = Total.L/1000)%>%
dplyr::rename(Diet=Food)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"levels(tab_agar$Diet)[levels(tab_agar$Diet)=="HS"] ="HS (original, 1.5%)"Error in levels(tab_agar$Diet)[levels(tab_agar$Diet) == "HS"] = "HS (original, 1.5%)": objet 'tab_agar' introuvablelevels(tab_agar$Diet)[levels(tab_agar$Diet)=="HY"] ="HY (original, 1.5%)"Error in levels(tab_agar$Diet)[levels(tab_agar$Diet) == "HY"] = "HY (original, 1.5%)": objet 'tab_agar' introuvableSample_size=
tab_agar%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_agar' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tab_agar)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_agar' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tab_agar) Error in is.data.frame(data): objet 'tab_agar' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tab_agar) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_agar' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("Any difference")),
Rep = nlevels(tab_agar$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_agar' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvablemod.gen = lmer(Total_Length_mm ~ Diet + (1 | Repeat), data = tab_agar)Error: bad 'data': objet 'tab_agar' introuvablemultcomp = glht(mod.gen, linfct=mcp(Diet="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=subset(tab_agar,!is.na(Total_Length_mm)),Total_Length_mm ~ Diet, max)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_agar' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Diet=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvable### Plot
Limits= c("HS Agar 0.5%", "HS Agar 1%", "HS (original, 1.5%)", "HS Agar 3%", "HY Agar 0.5%", "HY Agar 1%", "HY (original, 1.5%)", "HY Agar 3%")
cbbPalette = c("#FFB4B4", "#FFB4B4", "#FFB4B4", "#FFB4B4", "#C3E6FC", "#C3E6FC", "#C3E6FC", "#C3E6FC")
z = max(tab_agar$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_agar' introuvablePlot_Fig2S2B=
ggplot(tab_agar, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Total_Length_mm+0.4, label = Letter),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 1.5, y = 7.5, label = paste("p=",Pvalue)),size=3)+
scale_fill_manual(limits=Limits,
values=cbbPalette)+
scale_x_discrete("",
limits=Limits)+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=34,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_agar, aes(x = Diet, y = Total_Length_mm)): objet 'tab_agar' introuvablePlot_Fig2S2BError in eval(expr, envir, enclos): objet 'Plot_Fig2S2B' introuvableSorbitol, a nutritious but not palatable sugar, has increased size on HY compared to HS, while Arabinose, a palatable but not nutritious sugar, results in death of flies before reaching dissection day on HS, and decreased size of midguts on HY diet. Statistical analysis is HS vs HY for each sugar.
tab_xtrsugars_rev =
d[["2S2C"]]%>%
mutate(Total_Length_mm =Total.L/1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Day_of_Treatment=Day)%>%
mutate(Sugar=fct_relevel(Sugar,"Sucrose","Sorbitol", "Arabinose"))Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"#tab_xtrsugars_rev$Sugar = factor(c("Sucrose","Sorbitol","Arabinose"), levels = c("Sucrose", "Sorbitol", "Arabinose"))
Sample_size=
tab_xtrsugars_rev%>%
group_by(Diet,Sugar)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Sugar): objet 'tab_xtrsugars_rev' introuvable###Stats
# Sucrose:
mod.gen = fitme((Total_Length_mm) ~ Diet + (1 | Repeat), data = subset(tab_xtrsugars_rev,Sugar=="Sucrose"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_xtrsugars_rev' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((Total_Length_mm) ~ Diet + (1 / Repeat), data = subset(tab_xtrsugars_rev,Sugar=="Sucrose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_xtrsugars_rev' introuvablemod.gen1 = fitme((Total_Length_mm) ~ 1 + (1 | Repeat), data = subset(tab_xtrsugars_rev,Sugar=="Sucrose")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_xtrsugars_rev' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY Sucrose")),
Rep = nlevels(tab_lipids$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lipids' introuvabletab_stat_sucrose =tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Sorbitol:
mod.gen = fitme((Total_Length_mm) ~ Diet + (1 | Repeat), data = subset(tab_xtrsugars_rev,Sugar=="Sorbitol"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_xtrsugars_rev' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((Total_Length_mm) ~ Diet + (1 / Repeat), data = subset(tab_xtrsugars_rev,Sugar=="Sorbitol")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_xtrsugars_rev' introuvablemod.gen1 = fitme((Total_Length_mm) ~ 1 + (1 | Repeat), data = subset(tab_xtrsugars_rev,Sugar=="Sorbitol")) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_xtrsugars_rev' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY Sorbitol")),
Rep = nlevels(tab_lipids$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_lipids' introuvabletab_stat_Sorbitol=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat = rbind(tab_stat_sucrose,tab_stat_Sorbitol)Error in eval(quote(list(...)), env): objet 'tab_stat_sucrose' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat$Sugar = c("Sucrose","Sorbitol")Error in tab_stat$Sugar = c("Sucrose", "Sorbitol"): objet 'tab_stat' introuvabletab_stat$Sugar=as.factor(tab_stat$Sugar)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif.","Sugar"),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvableLimits = c("HS","HY")
Labels= c("HS","HY")
z = max(tab_xtrsugars_rev$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_xtrsugars_rev' introuvablePlot_Fig2S2C=
ggplot(tab_xtrsugars_rev, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z / 60) +
facet_grid(.~Sugar)+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.8, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat,aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 7.4), textsize = 3, vjust = -0.2, manual = TRUE)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=Limits,
labels=Labels)+
scale_y_continuous("Midgut length (mm)",
limits=c(1.7,7.5),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.background = element_blank(),
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_xtrsugars_rev, aes(x = Diet, y = Total_Length_mm)): objet 'tab_xtrsugars_rev' introuvablePlot_Fig2S2CError in eval(expr, envir, enclos): objet 'Plot_Fig2S2C' introuvable##Export Figure 2S2
Representative pictures of midguts from flies kept on HS (A) or HY (B) diet. Green arrows indicate intestinal stem cells (ISCs), marked only by GFP (green), red arrows mark enteroblasts (EBs), marked by GFP and GBE Su(H)-lacZ (red), and white arrow indicate enteroendocrine (EE) cells, marked with anti-Prospero antibody (white). All nuclei are stained with DAPI (blue). Complete graphical annotation can be found in manuscript figures
Error in transpose(y): object is NULLError in rasterGrob(img3A): objet 'img3A' introuvableError in grid.draw(gob_imageFig3A): objet 'gob_imageFig3A' introuvableError in transpose(y): object is NULLError in rasterGrob(img3B): objet 'img3B' introuvableError in grid.draw(gob_imageFig3B): objet 'gob_imageFig3B' introuvableQuantification of total cell numbers in the posterior midgut (R4) for HS and HY
Tab_cellnumber =
d[["3C"]]%>%
mutate(across(c(Diet,Line,Day,Repeat,GutNumber,Region),as.factor))%>%
mutate(across(c(ISC.AL,EB.AL,EE.AL,EC.AL),round,0))Error in UseMethod("mutate"): pas de méthode pour 'mutate' applicable pour un objet de classe "NULL"###Stats
#### ISC
mod.gen = fitme(log(ISC.AL) ~ Diet + (1 | Repeat), data = Tab_cellnumber)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(ISC.AL) ~ Diet + (1 / Repeat), data = Tab_cellnumber) Error in is.data.frame(data): objet 'Tab_cellnumber' introuvablemod.gen1 = fitme(log(ISC.AL) ~ 1 + (1 | Repeat), data = Tab_cellnumber)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS vs HY ISC")),
Cell_type = as.character(paste("ISC.AL")),
Rep = nlevels(Tab_cellnumber$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_cellnumber' introuvabletab_stat_ISC=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#### EB
mod.gen = fitme(log(EB.AL) ~ Diet + (1 | Repeat),data = Tab_cellnumber)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(EB.AL) ~ Diet + (1 / Repeat),data = Tab_cellnumber) Error in is.data.frame(data): objet 'Tab_cellnumber' introuvablemod.gen1 = fitme(log(EB.AL) ~ 1 + (1 | Repeat), data = Tab_cellnumber) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS vs HY EB")),
Cell_type = as.character(paste("EB.AL")),
Rep = nlevels(Tab_cellnumber$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_cellnumber' introuvabletab_stat_EB=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#### EC
mod.gen = fitme(log(EC.AL) ~ Diet + (1 | Repeat), data = Tab_cellnumber)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(EC.AL) ~ Diet + (1 / Repeat), data = Tab_cellnumber) Error in is.data.frame(data): objet 'Tab_cellnumber' introuvablemod.gen1 = fitme(log(EC.AL) ~ 1 + (1 | Repeat), data = Tab_cellnumber) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvabletestfunction (pkg = ".", filter = NULL, stop_on_failure = FALSE,
export_all = TRUE, ...)
{
save_all()
pkg <- as.package(pkg)
if (!uses_testthat(pkg) && interactive()) {
cli::cli_alert_danger("No testing infrastructure found. Create it?")
if (utils::menu(c("Yes", "No")) == 1) {
usethis_use_testthat(pkg)
}
return(invisible())
}
load_all(pkg$path)
cli::cli_alert_info("Testing {.pkg {pkg$package}}")
withr::local_envvar(r_env_vars())
testthat::test_local(pkg$path, filter = filter, stop_on_failure = stop_on_failure,
...)
}
<bytecode: 0x000000009e53be20>
<environment: namespace:devtools>Chi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS vs HY EC")),
Cell_type = as.character(paste("EC.AL")),
Rep = nlevels(Tab_cellnumber$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_cellnumber' introuvabletab_stat_EC=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#### EE
mod.gen = fitme(log(EE.AL) ~ Diet + (1 | Repeat), data = Tab_cellnumber)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(EE.AL) ~ Diet + (1 / Repeat), data = Tab_cellnumber) Error in is.data.frame(data): objet 'Tab_cellnumber' introuvablemod.gen1 = fitme(log(EE.AL) ~ 1 + (1 | Repeat), data = Tab_cellnumber) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Tab_cellnumber' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS vs HY EE")),
Cell_type = as.character(paste("EE.AL")),
Rep = nlevels(Tab_cellnumber$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_cellnumber' introuvabletab_stat_EE=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_ISC,tab_stat_EB,tab_stat_EC,tab_stat_EE)Error in eval(quote(list(...)), env): objet 'tab_stat_ISC' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Cell type", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Cell number) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Cell type", "Replicates", : objet 'tab_stat' introuvable### Plot
Limits = c("HS", "HY")
Tab_cellnumber_gather=
Tab_cellnumber %>%
select(Diet,Line,Day,Repeat,GutNumber,Region,EB.AL,ISC.AL,EE.AL,EC.AL)%>%
gather(key, value, -c(Diet,Line,Day,Repeat,GutNumber,Region)) %>%
dplyr::rename(Cell_type = key,
Cell_number = value) %>%
mutate_if(is.character,as.factor)Error in select(., Diet, Line, Day, Repeat, GutNumber, Region, EB.AL, : objet 'Tab_cellnumber' introuvableSample_size=
subset(Tab_cellnumber_gather,!is.na(Day))%>%
group_by(Diet,Cell_type)%>%
summarise(Sample_size=n(),
max=max(Cell_number,na.rm=T))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Tab_cellnumber_gather' introuvabletmp=subset(Sample_size,Diet=="HY")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Sample_size' introuvabletab_stat =
left_join(tab_stat,tmp)Error in left_join(tab_stat, tmp): objet 'tab_stat' introuvableTreatment.status = c("ISC", "EB","EC","EE")
names(Treatment.status) = c("ISC.AL", "EB.AL","EC.AL","EE.AL")
Plot_Fig3C=
ggplot(Tab_cellnumber_gather, aes(x = Diet, y = Cell_number/100*2))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center") +
facet_wrap(.~Cell_type,scale="free_y",labeller=labeller(Cell_type=Treatment.status))+
geom_blank(data=tab_stat, aes(y = max/100*2.5))+
geom_signif(data = tab_stat, aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = max/100*2.2,), textsize = 3, vjust = -0.2, manual = TRUE)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS", "HY"),
labels=c("HS (n = 46)", "HY (n = 55)"))+
scale_y_continuous(expression(paste("Cell number in posterior midgut (x",10^2,")",sep="")))+
stat_summary(fun = mean, geom = "point", size = 2.5, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 1.5, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Tab_cellnumber_gather, aes(x = Diet, y = Cell_number/100 * : objet 'Tab_cellnumber_gather' introuvablePlot_Fig3CError in eval(expr, envir, enclos): objet 'Plot_Fig3C' introuvableHS and HY diets do not affect the relative proportion of cell types in the midgut (error is standard error of the mean).
tab_prop_cell_type =
d[["3C"]]%>%
dplyr::select(Diet, Line, Day, Repeat, GutNumber, Region | ends_with(".AL") & !starts_with("ESG"))%>%
mutate_if(is.character,as.factor)%>%
drop_na()%>%
mutate(across(c(ISC.AL,EB.AL,EE.AL,EC.AL),round,0))%>%
mutate(Total_cell=ISC.AL+EB.AL+EE.AL+EC.AL,
proportion_ISC=ISC.AL/Total_cell*100,
proportion_EB=EB.AL/Total_cell*100,
proportion_EE=EE.AL/Total_cell*100,
proportion_EC=EC.AL/Total_cell*100)%>%
dplyr::select(Diet, Line, Day, Repeat, GutNumber, Region | starts_with("proportion"))%>%
gather(key, value, -!starts_with("proportion") )%>%
dplyr::rename(Cell_type = key,
Cell_proportion = value) %>%
mutate_if(is.character,as.factor) %>%
group_by(Diet,Cell_type)%>%
summarise(mean_proportion=mean(Cell_proportion, na.rm=T),
se_proportion=se(Cell_proportion)) %>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'select' applicable pour un objet de classe "NULL"for (i in 1:length(tab_prop_cell_type$se_proportion)){
tab_prop_cell_type$se_proportionGraphPlus[i] = tab_prop_cell_type$mean_proportion[i]+tab_prop_cell_type$se_proportion[i]
tab_prop_cell_type$se_proportionGraphMinus[i] = tab_prop_cell_type$mean_proportion[i]-tab_prop_cell_type$se_proportion[i]
}Error in eval(expr, envir, enclos): objet 'tab_prop_cell_type' introuvablefor (i in 1:length(tab_prop_cell_type$se_proportion)){
if(tab_prop_cell_type$Cell_type[i]=="proportion_EB"){
tab_prop_cell_type$se_proportionGraphPlus[i] = tab_prop_cell_type$mean_proportion[i]+tab_prop_cell_type$se_proportion[i]
tab_prop_cell_type$se_proportionGraphMinus[i] = tab_prop_cell_type$mean_proportion[i]-tab_prop_cell_type$se_proportion[i]
}else{
if(tab_prop_cell_type$Cell_type[i]=="proportion_EC"){
tab_prop_cell_type$se_proportionGraphPlus[i] = tab_prop_cell_type$mean_proportion[i-1]+tab_prop_cell_type$mean_proportion[i]+tab_prop_cell_type$se_proportion[i]
tab_prop_cell_type$se_proportionGraphMinus[i] = tab_prop_cell_type$mean_proportion[i-1]+tab_prop_cell_type$mean_proportion[i]+-tab_prop_cell_type$se_proportion[i]
}else{
if(tab_prop_cell_type$Cell_type[i]=="proportion_EE"){
tab_prop_cell_type$se_proportionGraphPlus[i] =tab_prop_cell_type$mean_proportion[i-1]+ tab_prop_cell_type$mean_proportion[i-2]+tab_prop_cell_type$mean_proportion[i]+tab_prop_cell_type$se_proportion[i]
tab_prop_cell_type$se_proportionGraphMinus[i] =tab_prop_cell_type$mean_proportion[i-1]+ tab_prop_cell_type$mean_proportion[i-2]+tab_prop_cell_type$mean_proportion[i]-tab_prop_cell_type$se_proportion[i]
}else{
tab_prop_cell_type$se_proportionGraphPlus[i] =tab_prop_cell_type$mean_proportion[i-1]+tab_prop_cell_type$mean_proportion[i-2]+ tab_prop_cell_type$mean_proportion[i-3]+tab_prop_cell_type$mean_proportion[i]+tab_prop_cell_type$se_proportion[i]
tab_prop_cell_type$se_proportionGraphMinus[i] =tab_prop_cell_type$mean_proportion[i-1]+tab_prop_cell_type$mean_proportion[i-2]+ tab_prop_cell_type$mean_proportion[i-3]+tab_prop_cell_type$mean_proportion[i]-tab_prop_cell_type$se_proportion[i]
}
}
}
}Error in eval(expr, envir, enclos): objet 'tab_prop_cell_type' introuvabletab_prop_cell_type$Cell_type =factor(tab_prop_cell_type$Cell_type,levels = c("proportion_ISC","proportion_EE","proportion_EC","proportion_EB"))Error in factor(tab_prop_cell_type$Cell_type, levels = c("proportion_ISC", : objet 'tab_prop_cell_type' introuvablePlot_Fig3D =
ggplot(tab_prop_cell_type, aes(x=Diet, y=mean_proportion))+
geom_bar(stat="identity",aes(fill=Cell_type),color="black",width=.90)+
geom_errorbar(aes(ymin= se_proportionGraphMinus, ymax= se_proportionGraphPlus),width=0.25)+
scale_fill_manual(name = "Cell types",
values=c("#1fd511","#ffffff", "#5869d5","#fe0000"),
labels = c("ISC", "EE", "EC","EB"))+
scale_y_continuous("Proportion of cells (% \u00B1se)",
limits=c(0,101),
breaks=seq(0,100,by=25))+
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black", hjust = 0.1 ),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "bottom",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_prop_cell_type, aes(x = Diet, y = mean_proportion)): objet 'tab_prop_cell_type' introuvablePlot_Fig3DError in eval(expr, envir, enclos): objet 'Plot_Fig3D' introuvableDiet affects enterocyte size. Representative picture of midguts stained with anti-Mesh antibody on HS (D, left) vs HY (E, right) diet. Complete graphical annotation can be found in manuscript figures
Error in transpose(y): object is NULLError in rasterGrob(img3E): objet 'img3E' introuvableError in grid.draw(gob_imageFig3E): objet 'gob_imageFig3E' introuvableError in transpose(y): object is NULLError in rasterGrob(img3F): objet 'img3F' introuvableError in grid.draw(gob_imageFig3F): objet 'gob_imageFig3F' introuvableQuantification of EC size of individuals on HS or HY diet for 5 days confirms an increase in cell size on HY diet.
tab_cell_area =
d[["3G"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_cell_area%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_cell_area' introuvable###Stats
mod.gen = fitme(log(Area) ~ Diet + (1|Repeat),data =tab_cell_area)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_cell_area' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Area) ~ Diet + (1/Repeat),data =tab_cell_area)Error in is.data.frame(data): objet 'tab_cell_area' introuvablemod.gen1 = fitme(log(Area) ~ 1 + (1|Repeat),data =tab_cell_area)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_cell_area' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(tab_cell_area$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_cell_area' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Cell area) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
z = max(tab_cell_area$Area/1000, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_cell_area' introuvablePlot_Fig3G=
ggplot(tab_cell_area, aes(x = Diet, y = Area/1000))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/140) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -0.01, label = paste("(",Sample_size,")",sep="")),size=3)+
# geom_text(data = tab_stat, mapping = aes(x = 1.5, y = 0.62, label = paste("p=",format(Pvalue,digits=3))),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 0.86, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=c("HS", "HY"),
values= palette_diet_2 )+
scale_x_discrete("",
limits=c("HS", "HY"),
labels=c("HS", "HY"))+
scale_y_continuous(expression(paste("EC area (10"^3, "mm"^2,")",sep="")),
limits=c(-0.01,0.9),
breaks=seq(0,0.8,by=0.1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_cell_area, aes(x = Diet, y = Area/1000)): objet 'tab_cell_area' introuvablePlot_Fig3GError in eval(expr, envir, enclos): objet 'Plot_Fig3G' introuvable##Export Figure 3
ECs are more densely packed on HS diet than on HY diet.
tab_ECarea =
d[["3C"]]%>%
select(Diet, Line, Day, Repeat, GutNumber, Region,EC.A)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(EC_density=EC.A)%>%
mutate(EC_density_mm=EC_density*1000)%>%
drop_na()Error in UseMethod("select"): pas de méthode pour 'select' applicable pour un objet de classe "NULL"Sample_size=
tab_ECarea%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_ECarea' introuvable###Stats
mod.gen = fitme(EC_density_mm ~ Diet + (1 | Repeat), data = tab_ECarea)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_ECarea' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(EC_density_mm ~ Diet + (1 / Repeat), data = tab_ECarea) Error in is.data.frame(data): objet 'tab_ECarea' introuvablemod.gen1 = fitme(EC_density_mm ~ 1 + (1 | Repeat), data = tab_ECarea) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_ECarea' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(tab_ECarea$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_ECarea' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("EC density ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvableLimits= c("HS","HY")
z=max(tab_ECarea$EC_density_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_ECarea' introuvablePlot_Fig3S1A =
ggplot(tab_ECarea, aes(x=Diet, y=EC_density_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.8, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 9, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS", "HY"),
labels=c("HS", "HY"))+
scale_y_continuous(expression(paste("EC density (per ",mm^2,")")),
limits=c(1.5,9.5),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_ECarea, aes(x = Diet, y = EC_density_mm)): objet 'tab_ECarea' introuvablePlot_Fig3S1AError in eval(expr, envir, enclos): objet 'Plot_Fig3S1A' introuvableScheme illustrating area measurements. Top view in this scheme is as in pictures shown in figure 3 D, E. 3D side view show side view with Mesh showing measured surface.
Error in transpose(y): object is NULLError in rasterGrob(img3S1B): objet 'img3S1B' introuvableError in grid.draw(gob_imageFig3S1B): objet 'gob_imageFig3S1B' introuvableDiet affects enterocyte size. Quantification of EC height of MyoTS>GFP on HS or HY diet demonstrates an increase in cell height on HY diet.
tab_ECheight =
d[["3 - S1C"]]%>%
select(Diet, Repeat, GutNumber, Region, Height)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(EC_height=Height)%>%
drop_na()Error in UseMethod("select"): pas de méthode pour 'select' applicable pour un objet de classe "NULL"tab_ECheight$EC_height <- as.numeric(tab_ECheight$EC_height)Error in eval(expr, envir, enclos): objet 'tab_ECheight' introuvableSample_size=
tab_ECheight%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_ECheight' introuvable###Stats
mod.gen = fitme((EC_height) ~ Diet + (1 | Repeat), data = tab_ECheight)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_ECheight' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(EC_height ~ Diet + (1 / Repeat), data = tab_ECheight) Error in is.data.frame(data): objet 'tab_ECheight' introuvablemod.gen1 = fitme(EC_height ~ 1 + (1 | Repeat), data = tab_ECheight) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_ECheight' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvable#Now we make a tab with the results
tab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(tab_ECheight$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_ECheight' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("EC height ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvableLimits= c("HS","HY")
z=max(tab_ECheight$EC_height, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_ECheight' introuvablePlot_Fig3S1C =
ggplot(tab_ECheight, aes(x=Diet, y=EC_height))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/150) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -1, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 23, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=Limits,
values=palette_diet_2)+
scale_x_discrete("",
limits=c("HS", "HY"),
labels=c("HS", "HY"))+
scale_y_continuous(expression(paste("EC height (", mu, "m)")),
limits=c(-2,25),
breaks=seq(2,25,by=5))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_ECheight, aes(x = Diet, y = EC_height)): objet 'tab_ECheight' introuvablePlot_Fig3S1CError in eval(expr, envir, enclos): objet 'Plot_Fig3S1C' introuvableRepresentative density plot from FACS for HS diet Complete annotation found in manuscript’s figures
Error in transpose(y): object is NULLError in rasterGrob(img3S1D): objet 'img3S1D' introuvableError in grid.draw(gob_imageFig3S1D): objet 'gob_imageFig3S1D' introuvableRepresentative density plot from FACS for HY diet Complete annotation found in manuscript’s figures
Error in transpose(y): object is NULLError in rasterGrob(img3S1E): objet 'img3S1E' introuvableError in grid.draw(gob_imageFig3S1E): objet 'gob_imageFig3S1E' introuvableRepresentative frequency plot from FACS for HS diet. Complete annotation found in manuscript’s figures
Error in transpose(y): object is NULLError in rasterGrob(img3S1F): objet 'img3S1F' introuvableError in grid.draw(gob_imageFig3S1F): objet 'gob_imageFig3S1F' introuvableRepresentative frequency plot from FACS for HY dietComplete annotation found in manuscript’s figures
Error in transpose(y): object is NULLError in rasterGrob(img3S1G): objet 'img3S1G' introuvableError in grid.draw(gob_imageFig3S1G): objet 'gob_imageFig3S1G' introuvablePloidy of midguts on either HS or HY diets is largely unchanged. Stacked bar plot from 7 repeats, each of 25 midguts
tab_ploidy_rev =
d[["3 - S1H"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
group_by(Diet, Ploidy)%>%
summarise(mean_Percentage=mean(Percentage,na.rm=T),
sd_Percentage=sd(Percentage))%>%
mutate(group=paste(Diet, Ploidy,sep="_"))%>%
mutate(Ploidy=fct_relevel(Ploidy,"2","4", "8", "16", "32", "64", "64+"))%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_ploidy_rev%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in is_grouped_df(tbl): objet 'tab_ploidy_rev' introuvable# Creation of dataset with right position for error bar
##HS
tmp = subset(tab_ploidy_rev , Diet%in%c("HS"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ploidy_rev' introuvabletmp1 <- subset(tmp, select = -c(group , sd_Percentage, Diet))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmp' introuvabletmpw1 <-spread(tmp1, Ploidy, mean_Percentage)Error in spread(tmp1, Ploidy, mean_Percentage): objet 'tmp1' introuvabletmpw1$`2.p` = tmpw1$`2`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`4.p` = tmpw1$`2` + tmpw1$`4`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`8.p` = tmpw1$`4.p` + tmpw1$`8`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`16.p` = tmpw1$`8.p` + tmpw1$`16`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`32.p` = tmpw1$`16.p` + tmpw1$`32`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64.p` = tmpw1$`32.p` + tmpw1$`64`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64+.p` = tmpw1$`64.p` + tmpw1$`64+`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmp2 <- subset(tmp, select = -c(group , mean_Percentage, Diet))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmp' introuvabletmpw2 <-spread(tmp2, Ploidy, sd_Percentage)Error in spread(tmp2, Ploidy, sd_Percentage): objet 'tmp2' introuvabletmpw1$`2.se` = tmpw2$`2`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`4.se` = tmpw2$`4`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`8.se` = tmpw2$`8`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`16.se` = tmpw2$`16`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`32.se` = tmpw2$`32`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`64.se` = tmpw2$`64`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`64+.se` = tmpw2$`64+`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`2.se+` = tmpw1$`2` + tmpw1$`2.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`4.se+` = tmpw1$`4.p` + tmpw1$`4.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`8.se+` = tmpw1$`8.p` + tmpw1$`8.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`16.se+` = tmpw1$`16.p` + tmpw1$`16.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`32.se+` = tmpw1$`32.p` + tmpw1$`32.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64.se+` = tmpw1$`64.p` + tmpw1$`64.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64+.se+` = tmpw1$`64+.p` + tmpw1$`64+.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`2.se-` = tmpw1$`2` - tmpw1$`2.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`4.se-` = tmpw1$`4.p` - tmpw1$`4.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`8.se-` = tmpw1$`8.p` - tmpw1$`8.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`16.se-` = tmpw1$`16.p` - tmpw1$`16.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`32.se-` = tmpw1$`32.p` - tmpw1$`32.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64.se-` = tmpw1$`64.p` - tmpw1$`64.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64+.se-` = tmpw1$`64+.p` - tmpw1$`64+.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpl <- reshape(data=tmpw1,
varying = list(Ploidy = c(1:7), Position = c(8:14), se = c(15:21), seplus = c(22:28), seminus = c(29:35)),
direction = 'long',
v.names = c("Percentage", "Position", "se", "seplus", "seminus"),
sep = ".")Error in FUN(X[[i]], ...): objet 'tmpw1' introuvabletmpl$Ploidy = c("2","4", "8", "16", "32", "64", "64+")Error in tmpl$Ploidy = c("2", "4", "8", "16", "32", "64", "64+"): objet 'tmpl' introuvabletmpl$Diet = "HS"Error in tmpl$Diet = "HS": objet 'tmpl' introuvabletmpl <- subset(tmpl, select = -c(time , id))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpl' introuvabletmpl_HS <- tmplError in eval(expr, envir, enclos): objet 'tmpl' introuvable##HY
tmp = subset(tab_ploidy_rev , Diet%in%c("HY"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ploidy_rev' introuvabletmp1 <- subset(tmp, select = -c(group , sd_Percentage, Diet))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmp' introuvabletmpw1 <-spread(tmp1, Ploidy, mean_Percentage)Error in spread(tmp1, Ploidy, mean_Percentage): objet 'tmp1' introuvabletmpw1$`2.p` = tmpw1$`2`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`4.p` = tmpw1$`2` + tmpw1$`4`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`8.p` = tmpw1$`4.p` + tmpw1$`8`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`16.p` = tmpw1$`8.p` + tmpw1$`16`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`32.p` = tmpw1$`16.p` + tmpw1$`32`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64.p` = tmpw1$`32.p` + tmpw1$`64`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64+.p` = tmpw1$`64.p` + tmpw1$`64+`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmp2 <- subset(tmp, select = -c(group , mean_Percentage, Diet))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmp' introuvabletmpw2 <-spread(tmp2, Ploidy, sd_Percentage)Error in spread(tmp2, Ploidy, sd_Percentage): objet 'tmp2' introuvabletmpw1$`2.se` = tmpw2$`2`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`4.se` = tmpw2$`4`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`8.se` = tmpw2$`8`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`16.se` = tmpw2$`16`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`32.se` = tmpw2$`32`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`64.se` = tmpw2$`64`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`64+.se` = tmpw2$`64+`Error in eval(expr, envir, enclos): objet 'tmpw2' introuvabletmpw1$`2.se+` = tmpw1$`2` + tmpw1$`2.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`4.se+` = tmpw1$`4.p` + tmpw1$`4.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`8.se+` = tmpw1$`8.p` + tmpw1$`8.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`16.se+` = tmpw1$`16.p` + tmpw1$`16.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`32.se+` = tmpw1$`32.p` + tmpw1$`32.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64.se+` = tmpw1$`64.p` + tmpw1$`64.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64+.se+` = tmpw1$`64+.p` + tmpw1$`64+.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`2.se-` = tmpw1$`2` - tmpw1$`2.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`4.se-` = tmpw1$`4.p` - tmpw1$`4.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`8.se-` = tmpw1$`8.p` - tmpw1$`8.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`16.se-` = tmpw1$`16.p` - tmpw1$`16.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`32.se-` = tmpw1$`32.p` - tmpw1$`32.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64.se-` = tmpw1$`64.p` - tmpw1$`64.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpw1$`64+.se-` = tmpw1$`64+.p` - tmpw1$`64+.se`Error in eval(expr, envir, enclos): objet 'tmpw1' introuvabletmpl <- reshape(data=tmpw1,
varying = list(Ploidy = c(1:7), Position = c(8:14), se = c(15:21), seplus = c(22:28), seminus = c(29:35)),
direction = 'long',
v.names = c("Percentage", "Position", "se", "seplus", "seminus"),
sep = ".")Error in FUN(X[[i]], ...): objet 'tmpw1' introuvabletmpl$Ploidy = c("2","4", "8", "16", "32", "64", "64+")Error in tmpl$Ploidy = c("2", "4", "8", "16", "32", "64", "64+"): objet 'tmpl' introuvabletmpl$Diet = "HY"Error in tmpl$Diet = "HY": objet 'tmpl' introuvabletmpl <- subset(tmpl, select = -c(time , id))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpl' introuvabletmpl_HY <- tmplError in eval(expr, envir, enclos): objet 'tmpl' introuvable#Bind, rename and reorcer
tab_ploidy <- rbind(tmpl_HS, tmpl_HY)Error in eval(quote(list(...)), env): objet 'tmpl_HS' introuvabletab_ploidy$Ploidy <- as.factor(tab_ploidy$Ploidy)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_ploidy' introuvabletab_ploidy$Ploidy <-factor(tab_ploidy$Ploidy, levels =c("64+","64", "32", "16", "8", "4", "2"))Error in factor(tab_ploidy$Ploidy, levels = c("64+", "64", "32", "16", : objet 'tab_ploidy' introuvable#Plot
Plot_Fig3S1H =
ggplot(tab_ploidy, aes(x=Diet, y=Percentage))+
geom_bar(stat="identity",aes(fill=Ploidy),color="black",width=.90)+
geom_errorbar(aes(ymin= seminus, ymax= seplus),width=0.25, color = "black")+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -5, label = paste("(",Sample_size,")",sep="")),size=3)+
scale_fill_manual(name = "Ploidy",
values=c("#0052A2","#1A63AB", "#3375B5", "#6697C7", "#99BADA", "#CCDCEC", "#E6EEF6"),
labels = c("64+n", "64n", "32n", "16n", "8n", "4n", "2n"))+
scale_y_continuous("Percentage of ploidy (mean \u00B1sd)",
limits=c(-5,90),
breaks=seq(0,80,by=20))+
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = "bottom",
#legend.key.height = unit(0.6, "cm"),
#legend.key.width= unit(0.4, "cm"),
legend.title = element_blank(),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
strip.text = element_blank())+
guides(fill=guide_legend(nrow=4,byrow=TRUE))Error in ggplot(tab_ploidy, aes(x = Diet, y = Percentage)): objet 'tab_ploidy' introuvable #strip.background = element_rect(fill=NA, colour="black"),
#strip.placement="outside")
Plot_Fig3S1HError in eval(expr, envir, enclos): objet 'Plot_Fig3S1H' introuvable##Export Figure 3S1
Midguts can respond plastically to changes in isocaloric diets. Midgut length increases from eclosion on HY for 7 days, then decreases when switched to HS for additional 7 days but can re-increase size upon a further 7 days HY feeding. Letters above violin plots represent grouping by statistical differences (Post hoc Tukey on GLMM).
Length_plasticity_time =
d[["4A"]]%>%
mutate_at(vars(starts_with("Total")),~./1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Total_Length_mm=Total.L,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_plasticity_time%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'Length_plasticity_time' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = Length_plasticity_time)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_plasticity_time' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = Length_plasticity_time) Error in is.data.frame(data): objet 'Length_plasticity_time' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = Length_plasticity_time) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_plasticity_time' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Anova diets")),
Rep = nlevels(Length_plasticity_time$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_plasticity_time' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvablemod.gen = lmer(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = Length_plasticity_time)Error: bad 'data': objet 'Length_plasticity_time' introuvablemultcomp = glht(mod.gen, linfct=mcp(Diet="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=Length_plasticity_time,Total_Length_mm ~ Diet, max)Error in eval(m$data, parent.frame()): objet 'Length_plasticity_time' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Diet=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvable### Plot
Limits = c("Eclosion","HY","HYtoHS", "HYtoHStoHY")
z = max(Length_plasticity_time$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_plasticity_time' introuvablePlot_Fig4A=
ggplot(Length_plasticity_time, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Total_Length_mm+0.4, label = Letter),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 1.2, y = 7.5, label = paste("p=",format(Pvalue,digits=2))),size=3)+
scale_fill_manual(limits=Limits,
values=cbbPalette_4)+
scale_x_discrete("",
limits=Limits,
labels=c("Eclosion","HY","HY to HS", "HY to HS to HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(1.3,8.2),
breaks=seq(2,8,by=1),
minor_breaks = seq(3, 7,by= 1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_plasticity_time, aes(x = Diet, y = Total_Length_mm)): objet 'Length_plasticity_time' introuvablePlot_Fig4AError in eval(expr, envir, enclos): objet 'Plot_Fig4A' introuvableMitotically active cells visualized by phospho-Histone H3 (pH3) immunostaining are more numerous on HY diet than on HS diet. pH3+ cells gradually increase over time on HY, but not HS diet. Letters above violin plots represent grouping by statistical differences (Post hoc Tukey on GLMM).
Length_Diet_time =
d[["4B, 4S1C"]]%>%
mutate_at(vars(ends_with(".L")),~./1000)%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(group=paste(Diet, Day,sep="_"))%>%
dplyr::rename(Total_Length_mm=Total.L,
PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_Diet_time%>%
group_by(Diet,Day_of_treatment)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Day_of_treatment): objet 'Length_Diet_time' introuvable###Stats
mod.gen = fitme(PH3_positive_cell ~ group + (1 | Repeat),data = subset(Length_Diet_time,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Diet_time' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(PH3_positive_cell ~ group + (1 / Repeat),data = subset(Length_Diet_time,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Diet_time' introuvablemod.gen1 = fitme(PH3_positive_cell ~ 1 + (1 | Repeat),data = subset(Length_Diet_time,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Diet_time' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Any difference")),
Rep = nlevels(Length_Diet_time$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_Diet_time' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("PH3_positive_cell ~ group + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat$Diet="HS"Error in tab_stat$Diet = "HS": objet 'tab_stat' introuvablemod.gen = lmer(PH3_positive_cell ~ group + (1 | Repeat),data =subset(Length_Diet_time,!is.na(PH3_positive_cell)))Error: bad 'data': erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Diet_time' introuvablemultcomp = glht(mod.gen, linfct=mcp(group="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=subset(Length_Diet_time,!is.na(PH3_positive_cell)),PH3_positive_cell ~ group, max)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Diet_time' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$group=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvabletab_letter = separate(tab_letter,group, c("Diet", "Day_of_treatment"), sep = "_", remove=FALSE)Error in separate(tab_letter, group, c("Diet", "Day_of_treatment"), sep = "_", : objet 'tab_letter' introuvable### Plot
Limits = c("7","14","21", "28")
z = max(Length_Diet_time$PH3_positive_cell, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_Diet_time' introuvablePlot_Fig4B=
ggplot(Length_Diet_time, aes(x = Day_of_treatment, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
facet_grid(. ~ Diet)+
geom_text(data = Sample_size, mapping = aes(x = Day_of_treatment, y = -8, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Day_of_treatment, y = PH3_positive_cell+10, label = Letter),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 2, y = 130, label = paste("p=",format(Pvalue,digits=2))),size=3)+
scale_fill_manual(limits=c("HS","HY"),
values=palette_diet_2)+
scale_x_discrete("",
limits=Limits,
labels=c("7 days","14 days", "21 days", "28 days"))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-10,140),
breaks=seq(0,140,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_Diet_time, aes(x = Day_of_treatment, y = PH3_positive_cell)): objet 'Length_Diet_time' introuvablePlot_Fig4BError in eval(expr, envir, enclos): objet 'Plot_Fig4B' introuvableShifting between diets impacts pH3+ cell number in growth (HS to HY) experiments. Statistical comparisons are vs pre-shift measurement.
Length_Growth_PH3 =
d[["4C, 4S1D"]]%>%
mutate_at(vars(ends_with(".L")),~./1000)%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(Total_Length_mm=Total.L,
PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_Growth_PH3%>%
group_by(Diet,Dday)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Dday): objet 'Length_Growth_PH3' introuvable###Stats
###Day 7
mod.gen = fitme(log(PH3_positive_cell) ~ Diet + (1 | Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 7"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell) ~ Diet + (1 / Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 7"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvablemod.gen1 = fitme(log(PH3_positive_cell) ~ 1 + (1 | Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 7"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS Day 7 vs HS to HY Day 14")),
Variable = as.character(paste("Shift Day 7")),
Rep = nlevels(Length_Growth_PH3$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_Growth_PH3' introuvabletab_stat_7=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 14
mod.gen = fitme(log(PH3_positive_cell) ~ Diet + (1 | Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 14"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell) ~ Diet + (1 / Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 14"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvablemod.gen1 = fitme(log(PH3_positive_cell) ~ 1 + (1 | Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 14"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS Day 14 vs HS to HY Day 21")),
Variable = as.character(paste("Shift Day 14")),
Rep = nlevels(Length_Growth_PH3$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_Growth_PH3' introuvabletab_stat_14=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 21
mod.gen = fitme(log(PH3_positive_cell) ~ Diet + (1 | Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell) ~ Diet + (1 / Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvablemod.gen1 = fitme(log(PH3_positive_cell) ~ 1 + (1 | Repeat),data = subset(Length_Growth_PH3,Dday=="Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_Growth_PH3' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS Day 21 vs HS to HY Day 28")),
Variable = as.character(paste("Shift Day 21")),
Rep = nlevels(Length_Growth_PH3$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_Growth_PH3' introuvabletab_stat_21 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_7,tab_stat_14,tab_stat_21)Error in eval(quote(list(...)), env): objet 'tab_stat_7' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(PH3_positive_cell) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Variable", "Replicates", : objet 'tab_stat' introuvabletab_stat=
tab_stat %>%
dplyr::rename(Dday=Variable)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_stat' introuvable### Plot
Limits = c("HS","HStoHY")
z=max(Length_Growth_PH3$PH3_positive_cell, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_Growth_PH3' introuvablePlot_Fig4C=
ggplot(Length_Growth_PH3, aes(x = Diet, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
facet_grid(. ~ Dday)+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat, aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 132,), textsize = 3, vjust = -0.2, manual = TRUE)+
scale_fill_manual(limits=c("HS","HStoHY"),
values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=Limits,
labels=c("HS","HS to HY"))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-8,136),
breaks=seq(0,120,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_Growth_PH3, aes(x = Diet, y = PH3_positive_cell)): objet 'Length_Growth_PH3' introuvablePlot_Fig4CError in eval(expr, envir, enclos): objet 'Plot_Fig4C' introuvableShifting between diets impacts pH3+ cell number in shrinkage (HY to HS) experiments. Statistical comparisons are vs pre-shift measurement.
Length_shrinkage_PH3 =
d[["4C', 4S1D'"]]%>%
mutate_at(vars(ends_with(".L")),~./1000)%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(Total_Length_mm=Total.L,
PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_shrinkage_PH3%>%
group_by(Diet,Dday)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Dday): objet 'Length_shrinkage_PH3' introuvable###Stats
###Day 7
mod.gen = fitme(log(PH3_positive_cell) ~ Diet + (1 | Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 7"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell) ~ Diet + (1 / Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 7"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvablemod.gen1 = fitme(log(PH3_positive_cell) ~ 1 + (1 | Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 7"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_shrinkage = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS Day 7 vs HS to HY Day 14")),
Variable = as.character(paste("Shift Day 7")),
Rep = nlevels(Length_shrinkage_PH3$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_shrinkage,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'Length_shrinkage_PH3' introuvabletab_stat_7=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 14
mod.gen = fitme(log(PH3_positive_cell) ~ Diet + (1 | Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 14"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell) ~ Diet + (1 / Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 14"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvablemod.gen1 = fitme(log(PH3_positive_cell) ~ 1 + (1 | Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 14"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_shrinkage = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS Day 14 vs HS to HY Day 21")),
Variable = as.character(paste("Shift Day 14")),
Rep = nlevels(Length_shrinkage_PH3$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_shrinkage,df=1,lower.tail = F),digits=1)))Error in levels(x): objet 'Length_shrinkage_PH3' introuvabletab_stat_14=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 21
mod.gen = fitme(log(PH3_positive_cell) ~ Diet + (1 | Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell) ~ Diet + (1 / Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvablemod.gen1 = fitme(log(PH3_positive_cell) ~ 1 + (1 | Repeat),data = subset(Length_shrinkage_PH3,Dday=="Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shrinkage_PH3' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_shrinkage = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("HS Day 21 vs HS to HY Day 28")),
Variable = as.character(paste("Shift Day 21")),
Rep = nlevels(Length_shrinkage_PH3$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_shrinkage,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_shrinkage_PH3' introuvabletab_stat_21 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_7,tab_stat_14,tab_stat_21)Error in eval(quote(list(...)), env): objet 'tab_stat_7' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(PH3_positive_cell) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Variable", "Replicates", : objet 'tab_stat' introuvabletab_stat=
tab_stat %>%
dplyr::rename(Dday=Variable)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_stat' introuvable### Plot
Limits = c("HY","HYtoHS")
z = max(Length_shrinkage_PH3$PH3_positive_cell, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_shrinkage_PH3' introuvablePlot_Fig4D=
ggplot(Length_shrinkage_PH3, aes(x = Diet, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
facet_grid(. ~ Dday)+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat, aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 132,), textsize = 3, vjust = -0.2, manual = TRUE)+
scale_fill_manual(limits=c("HY","HYtoHS"),
values=cbbHY_HYtoHS)+
scale_x_discrete("",
limits=Limits,
labels=c("HY","HY to HS"))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-8,136),
breaks=seq(0,120,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_shrinkage_PH3, aes(x = Diet, y = PH3_positive_cell)): objet 'Length_shrinkage_PH3' introuvablePlot_Fig4DError in eval(expr, envir, enclos): objet 'Plot_Fig4D' introuvableClonal assay with EsgF/O system illustrates increased number of marked cells on HY (F) vs HS (E) diets 5 days post-eclosion in region 4 of the midgut. GFP, in green, marks all cells made since the EsgF/O system was activated. Complete graphical annotation can be found in manuscript figures
Error in transpose(y): object is NULLError in rasterGrob(img4E): objet 'img4E' introuvableError in grid.draw(gob_imageFig4E): objet 'gob_imageFig4E' introuvableError in transpose(y): object is NULLError in rasterGrob(img4F): objet 'img4F' introuvableError in grid.draw(gob_imageFig4F): objet 'gob_imageFig4F' introuvableCell loss assay enables analysis of the impact of diet composition on replacement ratio and rate. Description of experimental design is found in materials and methods and illustrated in figure 4–figure supplement 1H. In brief, this assay allows us to mark ECs and EBs at the start of the experiment and to count their numbers 14 days after shifting dietary conditions recapitulating growth and shrinkage of the midgut, thus estimating cell gain and cell loss in these conditions. Representative pictures for the cell loss assay in growing conditions (G, H, top row) and shrinkage conditions (I, J, bottom row). Complete graphical annotation can be found in manuscript figures
Error in transpose(y): object is NULLError in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"Error in grid.draw(gob_imageFig4G): objet 'gob_imageFig4G' introuvableError in transpose(y): object is NULLError in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"Error in grid.draw(gob_imageFig4H): objet 'gob_imageFig4H' introuvableError in transpose(y): object is NULLError in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"Error in grid.draw(gob_imageFig4I): objet 'gob_imageFig4I' introuvableError in transpose(y): object is NULLError in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"Error in grid.draw(gob_imageFig4J): objet 'gob_imageFig4J' introuvableIn red 5966GS> His-RFP, marking EB and EC. Number of ECs in the posterior midgut, both marked (Red, old ECs) and unmarked (Blue, new ECs) by RFP, error bars are SE from 3 repeats.
tab_prop_cell_RFP =
d[["4K"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
mutate(Post.Dapi.Number = (Post.Dapi.Number)*2)%>%
mutate(Post.RFP.Number = (Post.RFP.Number)*2)%>%
mutate(Post.NonRFP.Number = (Post.Dapi.Number - Post.RFP.Number))%>%
group_by(Day, Diet, Diet1, Experiment)%>%
summarise(mean_RFP_positive=mean(Post.RFP.Number,na.rm=T),
se_RFP_positive=se(Post.RFP.Number),
mean_RFP_negative=mean(Post.NonRFP.Number,na.rm=T),
se_RFP_negative=se(Post.NonRFP.Number))%>%
mutate(group=paste(Diet1,Experiment,sep="_"))%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"attach(tab_prop_cell_RFP)Error in attach(tab_prop_cell_RFP): objet 'tab_prop_cell_RFP' introuvablefor (i in 1:length(Experiment)){
tab_prop_cell_RFP$se_proportionGraphPlus_pos[i] = mean_RFP_positive[i]+se_RFP_positive[i]
tab_prop_cell_RFP$se_proportionGraphMinus_pos[i] = mean_RFP_positive[i]-se_RFP_positive[i]
tab_prop_cell_RFP$se_proportionGraphPlus_neg[i] = mean_RFP_positive[i]+mean_RFP_negative[i]+se_RFP_negative[i]
tab_prop_cell_RFP$se_proportionGraphMinus_neg[i] = mean_RFP_positive[i]+mean_RFP_negative[i]-se_RFP_negative[i]
}Error in eval(expr, envir, enclos): objet 'Experiment' introuvabletmp1 = tab_prop_cell_RFP[,c("Day", "Diet", "Diet1", "Experiment","mean_RFP_positive", "se_RFP_positive","se_proportionGraphPlus_pos", "se_proportionGraphMinus_pos")]Error in eval(expr, envir, enclos): objet 'tab_prop_cell_RFP' introuvabletmp1$RFP="Positive"Error in tmp1$RFP = "Positive": objet 'tmp1' introuvabletmp1=dplyr::rename(tmp1,mean_RFP = mean_RFP_positive,
se_RFP = se_RFP_positive,
se_proportionGraphPlus =se_proportionGraphPlus_pos,
se_proportionGraphMinus= se_proportionGraphMinus_pos)Error in dplyr::rename(tmp1, mean_RFP = mean_RFP_positive, se_RFP = se_RFP_positive, : objet 'tmp1' introuvabletmp2 = tab_prop_cell_RFP[,c("Day", "Diet", "Diet1", "Experiment","mean_RFP_negative", "se_RFP_negative", "se_proportionGraphMinus_neg" ,"se_proportionGraphPlus_neg")]Error in eval(expr, envir, enclos): objet 'tab_prop_cell_RFP' introuvabletmp2$RFP="Negative"Error in tmp2$RFP = "Negative": objet 'tmp2' introuvabletmp2=dplyr::rename(tmp2,mean_RFP = mean_RFP_negative,
se_RFP = se_RFP_negative,
se_proportionGraphPlus =se_proportionGraphPlus_neg,
se_proportionGraphMinus= se_proportionGraphMinus_neg)Error in dplyr::rename(tmp2, mean_RFP = mean_RFP_negative, se_RFP = se_RFP_negative, : objet 'tmp2' introuvabletab_prop_cell_RFP = rbind(tmp1,tmp2)Error in eval(quote(list(...)), env): objet 'tmp1' introuvabletab_prop_cell_RFP =
tab_prop_cell_RFP%>%
mutate_if(is.numeric,round,0)%>%
mutate_if(is.character,as.factor)Error in is_grouped_df(tbl): objet 'tab_prop_cell_RFP' introuvable#tab_prop_cell_RFP$Experiment = as.factor(ifelse(tab_prop_cell_RFP$Day=="0" & tab_prop_cell_RFP$Diet1=="HS","HS",
#ifelse(tab_prop_cell_RFP$Day=="0" & tab_prop_cell_RFP$Diet1=="HY","HY",
# as.character(tab_prop_cell_RFP$Experiment))))
#tab_prop_cell_RFP=
#tab_prop_cell_RFP%>%
#as.data.frame()%>%
#mutate(Diet1=fct_relevel(Diet1,"HS", "HStoHS" , "HStoHY", "HY", "HYtoHS", "HYtoHY"),
#Experiment=fct_relevel(Experiment, "HS", "Growth", "HY", "Shrinkage"))
levels(tab_prop_cell_RFP$Diet1) <- c("HS", "HS to HS" , "HS to HY", "HY", "HY to HS", "HY to HY")Error in levels(tab_prop_cell_RFP$Diet1) <- c("HS", "HS to HS", "HS to HY", : objet 'tab_prop_cell_RFP' introuvableSample_size=
d[["4K"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
group_by(Diet1)%>%
summarise(Sample_size=n())Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size$Experiment = c("G", "G", "G", "S", "S", "S")Error in Sample_size$Experiment = c("G", "G", "G", "S", "S", "S"): objet 'Sample_size' introuvablelevels(Sample_size$Diet1) <- c("HS", "HS to HS" , "HS to HY", "HY", "HY to HS", "HY to HY")Error in levels(Sample_size$Diet1) <- c("HS", "HS to HS", "HS to HY", : objet 'Sample_size' introuvablePlot_Fig4K =
ggplot(tab_prop_cell_RFP, aes(x=Diet1, y=mean_RFP))+
geom_bar(stat="identity",aes(fill=RFP),color="black",width=.90)+
geom_errorbar(aes(ymin= se_proportionGraphMinus, ymax= se_proportionGraphPlus),width=0.25)+
geom_text(data = Sample_size, mapping = aes(x = Diet1, y = 200, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_wrap(.~Experiment,scales="free_x")+
scale_fill_manual(name = "RFP labelling",
values=c("#3a5ecc","#cc0000"),
labels = c("Negative", "Positive"))+
scale_y_continuous("Number of cells (mean \u00B1se)",
limits=c(0,5800),
breaks=seq(0,5000,by=500))+
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = c(0.2,0.87),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
strip.text = element_blank())Error in ggplot(tab_prop_cell_RFP, aes(x = Diet1, y = mean_RFP)): objet 'tab_prop_cell_RFP' introuvable #strip.background = element_rect(fill=NA, colour="black"),
#strip.placement="outside")
Plot_Fig4KError in eval(expr, envir, enclos): objet 'Plot_Fig4K' introuvableData shown as rate relative to experiment start (cell /initial EC/ day). Number on bar in red is ratio of EC gained/EC lost (see materials and methods for formula).
tab_relative_cell_rate =
d[["4L, 4S2D"]]%>%
select(-starts_with("X"))%>%
drop_na()%>%
mutate_if(is.character,as.factor)%>%
group_by(Diet1, Experiment, Experiment2, GL)%>%
summarise(mean_RelativeRate=mean(RelativeRate,na.rm=T),
se_RelativeRate=se(RelativeRate))%>%
mutate(group=paste(Diet1,Experiment,sep="_"))%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'select' applicable pour un objet de classe "NULL"tab_relative_cell_rate_ratio =
tab_relative_cell_rate%>%
group_by(Diet1,Experiment2)%>%
summarize(Ratio = round(mean_RelativeRate[GL == "Gain"] / (-mean_RelativeRate[GL == "Loss"]),2))%>%
mutate(GL="Loss")Error in group_by(., Diet1, Experiment2): objet 'tab_relative_cell_rate' introuvablelevels(tab_relative_cell_rate$Diet1) <- c("HS to HS" , "HS to HY", "HY to HS", "HY to HY")Error in levels(tab_relative_cell_rate$Diet1) <- c("HS to HS", "HS to HY", : objet 'tab_relative_cell_rate' introuvablelevels(tab_relative_cell_rate_ratio$Diet1) <- c("HS to HS" , "HS to HY", "HY to HS", "HY to HY")Error in levels(tab_relative_cell_rate_ratio$Diet1) <- c("HS to HS", "HS to HY", : objet 'tab_relative_cell_rate_ratio' introuvablePlot_Fig4L =
ggplot(tab_relative_cell_rate, aes(x = Diet1, y = mean_RelativeRate, fill = GL))+
geom_bar(stat="identity",aes(fill=GL),color="black",width=.90)+
geom_hline(yintercept = 0)+
geom_text(data=tab_relative_cell_rate_ratio,mapping=aes(x=Diet1,y=-0.01,label=Ratio), color = "red")+
facet_grid(.~Experiment2,scales="free_x")+
scale_fill_manual(name = "Enterocyte",
values=c("palegreen", "moccasin"),
labels = c("Gain", "Loss"))+
scale_y_continuous("Cell rate (cell/ initialEC/ day)",
limits=c(-0.11,0.11),
breaks=seq(-0.2,0.2,by=0.05))+
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = c(0.18,0.83),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_relative_cell_rate, aes(x = Diet1, y = mean_RelativeRate, : objet 'tab_relative_cell_rate' introuvablePlot_Fig4LError in eval(expr, envir, enclos): objet 'Plot_Fig4L' introuvable##Export Figure 4
Midgut length increases progressively on HY, but not on HS. Statistics compare HS vs HY for each day, *** = p<0.01.
Length_dayseclosion =
d[["4 - S1A"]]%>%
select(-starts_with("X"))%>%
mutate_at(vars(starts_with("Total")),~./1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Total_Length_mm=Total.Length)%>%
mutate(group=paste(TreatCol,Day,sep="_"))Error in UseMethod("select"): pas de méthode pour 'select' applicable pour un objet de classe "NULL"Sample_size=
Length_dayseclosion%>%
group_by(Day,TreatCol)%>%
summarise(Sample_size=n())%>%
dplyr::rename(Diet=TreatCol)Error in group_by(., Day, TreatCol): objet 'Length_dayseclosion' introuvable#Stats4S1A
###Stats
#Day 1
tmp = subset(Length_dayseclosion, Day == "1") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosion' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character("1"),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_1 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 2
tmp = subset(Length_dayseclosion, Day == "2") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosion' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character("2"),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_2 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 3
tmp = subset(Length_dayseclosion, Day == "3") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosion' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character("3"),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_3 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 4
tmp = subset(Length_dayseclosion, Day == "4") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosion' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("4")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_4 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 5
tmp = subset(Length_dayseclosion, Day == "5") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosion' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character("5"),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_5 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat = rbind(tab_stat_day_1, tab_stat_day_2, tab_stat_day_3, tab_stat_day_4, tab_stat_day_5)Error in eval(quote(list(...)), env): objet 'tab_stat_day_1' introuvabletab_stat$padj = p.adjust(tab_stat$Pvalue, method = "BH")Error in p.adjust(tab_stat$Pvalue, method = "BH"): objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparisons diet within days", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparisons diet within days", "Replicates", : objet 'tab_stat' introuvabletab_stat =
tab_stat %>%
dplyr::rename(Day = Variable) %>%
mutate(Day = as.factor(Day))Error in dplyr::rename(., Day = Variable): objet 'tab_stat' introuvabletab_stat$Diet = "HY"Error in tab_stat$Diet = "HY": objet 'tab_stat' introuvableletter_position = aggregate(data = Length_dayseclosion, Total_Length_mm ~ Day, max)Error in eval(m$data, parent.frame()): objet 'Length_dayseclosion' introuvabletab_stat1 = left_join(tab_stat, letter_position)Error in left_join(tab_stat, letter_position): objet 'tab_stat' introuvable#Stats vs eclosion for HS
Length_dayseclosionHS = subset(Length_dayseclosion, Diet == "0" | Diet == "HS")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosion' introuvable#Day 1
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "1") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("1")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs1 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 2
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "2") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("2")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs2 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 3
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "3") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("3")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs3 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 4
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "4") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("4")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs4 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 5
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "5") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("5")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs5 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_statHSeclosion = rbind(tab_stat_day_0vs1, tab_stat_day_0vs2, tab_stat_day_0vs3, tab_stat_day_0vs4, tab_stat_day_0vs5)Error in eval(quote(list(...)), env): objet 'tab_stat_day_0vs1' introuvabletab_statHSeclosion$padj = p.adjust(tab_statHSeclosion$Pvalue, method = "BH")Error in p.adjust(tab_statHSeclosion$Pvalue, method = "BH"): objet 'tab_statHSeclosion' introuvabletab_statHSeclosion$sig = ifelse(tab_statHSeclosion$padj > 0.05, "ns",
ifelse(tab_statHSeclosion$padj < 0.05 & tab_statHSeclosion$padj > 0.01, "*",
ifelse(tab_statHSeclosion$padj < 0.01 & tab_statHSeclosion$padj > 0.001, "**",
ifelse(tab_statHSeclosion$padj < 0.001, "***", ""))))Error in ifelse(tab_statHSeclosion$padj > 0.05, "ns", ifelse(tab_statHSeclosion$padj < : objet 'tab_statHSeclosion' introuvabletab_statHSeclosion%>%
kable(col.names = c("Comparison to eclosion on HS", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Day + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison to eclosion on HS", "Replicates", : objet 'tab_statHSeclosion' introuvabletab_statHSeclosion =
tab_statHSeclosion %>%
dplyr::rename(Day = Variable) %>%
mutate(Day = as.factor(Day))Error in dplyr::rename(., Day = Variable): objet 'tab_statHSeclosion' introuvabletab_statHSeclosion$Diet = "HS"Error in tab_statHSeclosion$Diet = "HS": objet 'tab_statHSeclosion' introuvableletter_position = aggregate(data = Length_dayseclosion, Total_Length_mm ~ Day, max)Error in eval(m$data, parent.frame()): objet 'Length_dayseclosion' introuvabletab_statHSeclosion = left_join(tab_statHSeclosion, letter_position)Error in left_join(tab_statHSeclosion, letter_position): objet 'tab_statHSeclosion' introuvable#Stats vs eclosion for HY
Length_dayseclosionHS = subset(Length_dayseclosion, Diet == "0" | Diet == "HY")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosion' introuvable#Day 1
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "1") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("1")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs1 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 2
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "2") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("2")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs2 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 3
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "3") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("3")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs3 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 4
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "4") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("4")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs4 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Day 5
tmp = subset(Length_dayseclosionHS, Day == "0" | Day == "5") %>%
mutate(Day = as.factor(Day))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_dayseclosionHS' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2 * (mod.gen$APHLs[["p_v"]] - mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("5")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_day_0vs5 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_statHYeclosion = rbind(tab_stat_day_0vs1, tab_stat_day_0vs2, tab_stat_day_0vs3, tab_stat_day_0vs4, tab_stat_day_0vs5)Error in eval(quote(list(...)), env): objet 'tab_stat_day_0vs1' introuvabletab_statHYeclosion$padj = as.numeric(p.adjust(tab_statHYeclosion$Pvalue, method = "BH"))Error in p.adjust(tab_statHYeclosion$Pvalue, method = "BH"): objet 'tab_statHYeclosion' introuvabletab_statHYeclosion$sig = ifelse(tab_statHYeclosion$padj > 0.05, "ns",
ifelse(tab_statHYeclosion$padj < 0.05 & tab_statHYeclosion$padj > 0.01, "*",
ifelse(tab_statHYeclosion$padj < 0.01 & tab_statHYeclosion$padj > 0.001, "**",
ifelse(tab_statHYeclosion$padj < 0.001, "***", ""))))Error in ifelse(tab_statHYeclosion$padj > 0.05, "ns", ifelse(tab_statHYeclosion$padj < : objet 'tab_statHYeclosion' introuvabletab_statHYeclosion%>%
kable(col.names = c("Comparison to eclosion on HY", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Day + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison to eclosion on HY", "Replicates", : objet 'tab_statHYeclosion' introuvabletab_statHYeclosion =
tab_statHYeclosion %>%
dplyr::rename(Day = Variable) %>%
mutate(Day = as.factor(Day))Error in dplyr::rename(., Day = Variable): objet 'tab_statHYeclosion' introuvabletab_statHYeclosion$Diet = "HY"Error in tab_statHYeclosion$Diet = "HY": objet 'tab_statHYeclosion' introuvableletter_position = aggregate(data = Length_dayseclosion, Total_Length_mm ~ Day, max)Error in eval(m$data, parent.frame()): objet 'Length_dayseclosion' introuvabletab_statHYeclosion = left_join(tab_statHYeclosion, letter_position)Error in left_join(tab_statHYeclosion, letter_position): objet 'tab_statHYeclosion' introuvable### Plot
z = max(Length_dayseclosion$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_dayseclosion' introuvablePlot_Fig4S1A=
ggplot(Length_dayseclosion, aes(x = Day, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
facet_grid(.~Diet,scales="free_x",space="free")+
geom_text(data = Sample_size, mapping = aes(x = Day, y = 2.3, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_stat1, mapping = aes(x =Day, y = 7.5, label = sig),size=3)+
geom_text(data = tab_statHSeclosion, mapping = aes(x =Day, y = 3.5, label = sig),size=3)+
geom_text(data = tab_statHYeclosion, mapping = aes(x =Day, y = 3.5, label = sig),size=3)+
scale_fill_manual(limits=c("0","HS","HY"),
values= c("#cfe7cf","#FFB4B4", "#C3E6FC"))+
scale_x_discrete("Days post eclosion")+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8.2),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_dayseclosion, aes(x = Day, y = Total_Length_mm)): objet 'Length_dayseclosion' introuvablePlot_Fig4S1AError in eval(expr, envir, enclos): objet 'Plot_Fig4S1A' introuvableScheme for Figure 4 B, C, D and Figure 4 supplement 1C, D, E. At eclosion, flies were allocated to either HS or HY diet. 7-, 14- and 21-days post eclosion flies were either kept on the same diet or shifted on the opposite diet for 7 days (HS to HY or HY to HS). Flies were dissected every 7 days, up until day 28.
img4S1B = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/4 - S1B.jpg") Error in transpose(y): object is NULLgob_imageFig4S1B = rasterGrob(img4S1B)Error in rasterGrob(img4S1B): objet 'img4S1B' introuvablegrid.draw(gob_imageFig4S1B)Error in grid.draw(gob_imageFig4S1B): objet 'gob_imageFig4S1B' introuvableHS diet does not postpone post-eclosion development, but rather induces continual midgut shrinkage over 28 days of feeding. Letters above violin plots represent grouping by statistical differences (Post hoc Tukey on GLMM).
Length_longshift =
d[["4B, 4S1C"]]%>%
select(-Total.PH3)%>%
mutate(Total_Length_mm = Total.L/1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Day_of_treatment=Day)Error in UseMethod("select"): pas de méthode pour 'select' applicable pour un objet de classe "NULL"Sample_size=
Length_longshift%>%
group_by(Day_of_treatment,Diet)%>%
summarise(Sample_size=n())Error in group_by(., Day_of_treatment, Diet): objet 'Length_longshift' introuvable###Stats
#HS
tmp= subset(Length_longshift, Diet=="HS")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_longshift' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day_of_treatment + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day_of_treatment + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Diet = as.character(paste("HS")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_HS= tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvablemod.gen = lmer(log(Total_Length_mm) ~ Day_of_treatment + (1 | Repeat), data = tmp)Error: bad 'data': objet 'tmp' introuvablemultcomp = glht(mod.gen, linfct=mcp(Day_of_treatment="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!Comp_HS = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position_HS = aggregate(data=tmp,Total_Length_mm ~ Day_of_treatment, max)Error in eval(m$data, parent.frame()): objet 'tmp' introuvableletter_position_HS$Diet="HS"Error in letter_position_HS$Diet = "HS": objet 'letter_position_HS' introuvable#HY
tmp= subset(Length_longshift, Diet=="HY")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_longshift' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Day_of_treatment + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Day_of_treatment + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Diet = as.character(paste("HY")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_HY =tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvablemod.gen = lmer(log(Total_Length_mm) ~ Day_of_treatment + (1 | Repeat), data = tmp)Error: bad 'data': objet 'tmp' introuvablemultcomp = glht(mod.gen, linfct=mcp(Day_of_treatment="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!Comp_HY = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position_HY = aggregate(data=tmp,Total_Length_mm ~ Day_of_treatment, max)Error in eval(m$data, parent.frame()): objet 'tmp' introuvableletter_position_HY$Diet="HY"Error in letter_position_HY$Diet = "HY": objet 'letter_position_HY' introuvabletab_stat = rbind(tab_stat_HS,tab_stat_HY)Error in eval(quote(list(...)), env): objet 'tab_stat_HS' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Any difference", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Day + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Any difference", "Replicates", "Chi2", : objet 'tab_stat' introuvableletter_position = rbind(letter_position_HS,letter_position_HY)Error in eval(quote(list(...)), env): objet 'letter_position_HS' introuvabletab_letter_HS = as.data.frame(Comp_HS$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'Comp_HS' introuvabletab_letter_HS$Diet = "HS"Error in tab_letter_HS$Diet = "HS": objet 'tab_letter_HS' introuvabletab_letter_HS$Day_of_treatment=rownames(tab_letter_HS)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter_HS' introuvablecolnames(tab_letter_HS)[1] = "Letter"Error in colnames(tab_letter_HS)[1] = "Letter": objet 'tab_letter_HS' introuvabletab_letter_HY = as.data.frame(Comp_HY$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'Comp_HY' introuvabletab_letter_HY$Day_of_treatment=rownames(tab_letter_HY)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter_HY' introuvabletab_letter_HY$Diet = "HY"Error in tab_letter_HY$Diet = "HY": objet 'tab_letter_HY' introuvablecolnames(tab_letter_HY)[1] = "Letter"Error in colnames(tab_letter_HY)[1] = "Letter": objet 'tab_letter_HY' introuvabletab_letter = rbind(tab_letter_HS,tab_letter_HY)Error in eval(quote(list(...)), env): objet 'tab_letter_HS' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvable### Plot
z=max(Length_longshift$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_longshift' introuvablePlot_Fig4S1C=
ggplot(Length_longshift, aes(x = Day_of_treatment, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.15) +
facet_grid(.~Diet,scales="free_x",space="free")+
geom_text(data = Sample_size, mapping = aes(x = Day_of_treatment, y = 1.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Day_of_treatment, y = Total_Length_mm+0.4, label = Letter),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 1.5, y = 9.5, label = paste("p=",format(Pvalue,digits=2))),size=3)+
scale_fill_manual(limits=c("0","HS","HY"),
values= c("#cfe7cf","#FFB4B4", "#C3E6FC"))+
scale_x_discrete("Days post eclosion")+
scale_y_continuous("Midgut length (mm)",
limits=c(1.5,9.5),
breaks=seq(3,9,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_longshift, aes(x = Day_of_treatment, y = Total_Length_mm)): objet 'Length_longshift' introuvablePlot_Fig4S1CError in eval(expr, envir, enclos): objet 'Plot_Fig4S1C' introuvableMidgut size is a plastic, diet-dependent trait. Midguts of flies shifted between HS or HY can reversibly grow throughout 21 days. Statistical comparison is vs pre-shift measurement.
Length_shift_growth =
d[["4C, 4S1D"]]%>%
select(-Total.PH3)%>%
mutate(Total_Length_mm = Total.L/1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Day_of_treatment=Day)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'select' applicable pour un objet de classe "NULL"Sample_size=
Length_shift_growth%>%
group_by(Dday,Diet)%>%
summarise(Sample_size=n())Error in group_by(., Dday, Diet): objet 'Length_shift_growth' introuvable###Stats
# Day 7
tmp= subset(Length_shift_growth,Dday=="Shift Day 7")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shift_growth' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste(("HS Day 7 vs HS to HY Day 14"))),
Dday = as.character(paste("Shift Day 7")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_7 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Day 14
tmp= subset(Length_shift_growth,Dday=="Shift Day 14")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shift_growth' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste(("HS Day 14 vs HS to HY Day 21"))),
Dday = as.character(paste("Shift Day 14")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_14 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Day 21
tmp= subset(Length_shift_growth,Dday=="Shift Day 21")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shift_growth' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste(("HS Day 21 vs HS to HY Day 28"))),
Dday = as.character(paste("Shift Day 21")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_21 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_7,tab_stat_14,tab_stat_21)Error in eval(quote(list(...)), env): objet 'tab_stat_7' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Shift day", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Shift day", "Replicates", : objet 'tab_stat' introuvabletab_stat=
tab_stat%>%
mutate_if(is.character,as.factor)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_stat' introuvable### Plot
Treatment.status = c("Shift\nDay 7","Shift\nDay 14","Shift\nDay 21")
names(Treatment.status) = c("Shift Day 7", "Shift Day 14","Shift Day 21")
z=max(Length_shift_growth$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_shift_growth' introuvablePlot_Fig4S1D=
ggplot(Length_shift_growth, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
facet_grid(. ~ Dday,labeller=labeller(Dday=Treatment.status) )+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.6, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat, aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 9), textsize = 2.5, vjust = -0.2, manual = TRUE)+
scale_fill_manual(limits=c("HS","HStoHY"),
values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=c("HS","HStoHY"),
labels=c("HS","HS to HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(1.5,9.5),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 2.5, shape = 18,aes(group=Repeat, colour = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_shift_growth, aes(x = Diet, y = Total_Length_mm)): objet 'Length_shift_growth' introuvablePlot_Fig4S1DError in eval(expr, envir, enclos): objet 'Plot_Fig4S1D' introuvableMidgut size is a plastic, diet-dependent trait. Midguts of flies shifted between HS or HY can reversibly shrink throughout 21 days. Statistical comparison is vs pre-shift measurement.
Length_shift_Shrink =
d[["4C', 4S1D'"]]%>%
select(-Total.PH3)%>%
mutate(Total_Length_mm = Total.L/1000)%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Day_of_treatment=Day)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'select' applicable pour un objet de classe "NULL"Sample_size=
Length_shift_Shrink%>%
group_by(Dday,Diet)%>%
summarise(Sample_size=n())Error in group_by(., Dday, Diet): objet 'Length_shift_Shrink' introuvable###Stats
# Day 7
tmp= subset(Length_shift_Shrink,Dday=="Shift Day 7")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shift_Shrink' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste(("HS Day 7 vs HS to HY Day 14"))),
Dday = as.character(paste("Shift Day 7")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_7 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Day 14
tmp= subset(Length_shift_Shrink,Dday=="Shift Day 14")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shift_Shrink' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste(("HS Day 14 vs HS to HY Day 21"))),
Dday = as.character(paste("Shift Day 14")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_14 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable# Day 21
tmp= subset(Length_shift_Shrink,Dday=="Shift Day 21")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Length_shift_Shrink' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + (1 / Repeat), data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat), data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste(("HS Day 21 vs HS to HY Day 28"))),
Dday = as.character(paste("Shift Day 21")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_21 = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_7,tab_stat_14,tab_stat_21)Error in eval(quote(list(...)), env): objet 'tab_stat_7' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison","Shift day", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total length) ~ Day + Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Shift day", "Replicates", : objet 'tab_stat' introuvabletab_stat=
tab_stat%>%
mutate_if(is.character,as.factor)%>%
as.data.frame()%>%
mutate(Dday=fct_relevel(Dday,"Shift Day 7","Shift Day 14","Shift Day 21"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_stat' introuvable### Plot
Treatment.status = c("Shift\nDay 7","Shift\nDay 14","Shift\nDay 21")
names(Treatment.status) = c("Shift Day 7", "Shift Day 14","Shift Day 21")
z=max(Length_shift_Shrink$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'Length_shift_Shrink' introuvablePlot_Fig4S1E=
ggplot(Length_shift_Shrink, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.15) +
facet_grid(. ~ Dday,labeller=labeller(Dday=Treatment.status) )+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1.6, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat, aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 9), textsize = 2.5, vjust = -0.2, manual = TRUE)+
scale_fill_manual(limits=c("HY","HYtoHS"),
values=cbbHY_HYtoHS)+
scale_x_discrete("",
limits=c("HY","HYtoHS"),
labels=c("HY","HY to HS"))+
scale_y_continuous("Midgut length (mm)",
limits=c(1.5,9.5),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 2.5, shape = 18,aes(group=Repeat, colour = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_shift_Shrink, aes(x = Diet, y = Total_Length_mm)): objet 'Length_shift_Shrink' introuvablePlot_Fig4S1EError in eval(expr, envir, enclos): objet 'Plot_Fig4S1E' introuvableISC proliferation is promoted by yeast and antagonized by sugar. Cell proliferation (pH3 stain) is impeded by dietary sucrose, and increased by yeast, similar to total midgut length (Figure 2A). Plots showing counts of pH3+ cells as a function of ingested yeast and sucrose.
tab_nutri_geo_PH3 =
d[["4 - S1F"]]
jpeg(filename = "Plot_Fig4-S1F.jpeg",
res = 600,
width = 5, height = 4, units = 'in' )
par(cex=1, mar = c(4.5, 4.5, 1, 3))
with(tab_nutri_geo_PH3, geomPlotta(x = Sucrose.in.Diet, y = Yeast.in.Diet, z = Ph3.Total, alf = 1, xlim = c(-10, 300), ylim = c(-10, 300), xlab = "Sucrose in diet (g/L)", ylab = "Yeast in diet (g/L)", frame.plot= FALSE, cex.lab=1.2, cex.axis =1, las=1, labcex=1, asp=1))img4S1F = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/Plot_Fig4-S1F.jpeg") Error in transpose(y): object is NULLgob_imageFig4S1F = rasterGrob(img4S1F)Error in rasterGrob(img4S1F): objet 'img4S1F' introuvablegrid.draw(gob_imageFig4S1F)Error in grid.draw(gob_imageFig4S1F): objet 'gob_imageFig4S1F' introuvablePlots showing pH3+ cell counts increase with dietary yeast, with an optimum around HY diet. Increasing sucrose reduces counts of pH3+ cells.
tab_nutri_geo_PH3 =
d[["4 - S1F"]]
tab_nutri_geo_PH32 <- tab_nutri_geo_PH3 %>%
group_by(concatenate) %>%
summarize(Calories.ingested = mean(Calories.ingested),
Ph3.Total = mean(Ph3.Total),
Yeast.ingested = mean(Yeast.ingested),
Sucrose.ingested = mean(Sucrose.ingested))Error in UseMethod("group_by"): pas de méthode pour 'group_by' applicable pour un objet de classe "NULL"graph <- ggplot(tab_nutri_geo_PH32, aes(x=Sucrose.ingested, y=Yeast.ingested))Error in ggplot(tab_nutri_geo_PH32, aes(x = Sucrose.ingested, y = Yeast.ingested)): objet 'tab_nutri_geo_PH32' introuvablePlot_Fig4S1G=
graph + geom_point(aes(size=Calories.ingested, fill=Ph3.Total), stroke=1, shape=21, color="black") +
scale_size(range = c(1,5)) +
scale_fill_viridis_c() +
theme(plot.title= element_text(hjust = 0.5))+
scale_x_continuous("Sucrose ingested (g/L x Absorbance)",
limits=c(-5,160),
breaks=seq(0,160,by=25))+
scale_y_continuous("Yeast ingested (g/L x Absorbance)",
limits=c(-5,50),
breaks=seq(0,50,by=10))+
scale_size_continuous(range = c(1,5)) +
theme(panel.background = element_blank(),
panel.grid.major = element_line(colour = "black",linetype=3),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(c(0,0,0,0.5), "cm"),
legend.direction = "horizontal",
legend.box = "vertical",
legend.position = c(0.75,0.79),
legend.key.height = unit(0.3, "cm"),
legend.key.width= unit(0.3, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.box.background = element_rect(fill="white", colour ="black"),
legend.spacing.y = unit(0, "cm"))+
labs(fill = expression(paste("pH3" ^ "+", " cells")), size = "Calories
ingested", vjust="center" )Error in eval(expr, envir, enclos): objet 'graph' introuvablePlot_Fig4S1GError in eval(expr, envir, enclos): objet 'Plot_Fig4S1G' introuvable##Export Figure 4S1
Illustration of the cell loss assay (Figure 4G - L). A pulse of RU486 for 3 days marks all ECs and EBs through 5966GS>His-2BRFP. Flies were dissected at 2 and 16-days after cessation of hormone pulse.
img4S2A = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/4 - S2A.jpg") Error in transpose(y): object is NULLgob_imageFig4S2A = rasterGrob(img4S2A)Error in rasterGrob(img4S2A): objet 'img4S2A' introuvablegrid.draw(gob_imageFig4S2A)Error in grid.draw(gob_imageFig4S2A): objet 'gob_imageFig4S2A' introuvableHis2B-RFP is highly stable on both HS and HY diets on tissues not undergoing turnover in a manner similar to the midgut. We assayed the stability of the His2B-RFP by driving it through an ActGS driver, in the crop and hindgut in the same timeline as the experiment presented in Figure 4K. In both organs, we found a high degree of cells marked by His2B-RFP, and on both diets, at both the initial timepoint and after 14 days from the start of the chase. Day of dissection at the bottom of the chart are relative to start of pulse chase.
tab_Hisstab_rev =
d[["4S2B"]]%>%
mutate_at(vars(!starts_with("RFP")),as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"###Stats
#Crop
tmp = subset(tab_Hisstab_rev , Tissue%in%c("Crop"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_Hisstab_rev' introuvablemod.gen = fitme((RFP.Dapi) ~ Day * Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((RFP.Dapi) ~ Day * Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme((RFP.Dapi) ~ Day + Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvabletestfunction (pkg = ".", filter = NULL, stop_on_failure = FALSE,
export_all = TRUE, ...)
{
save_all()
pkg <- as.package(pkg)
if (!uses_testthat(pkg) && interactive()) {
cli::cli_alert_danger("No testing infrastructure found. Create it?")
if (utils::menu(c("Yes", "No")) == 1) {
usethis_use_testthat(pkg)
}
return(invisible())
}
load_all(pkg$path)
cli::cli_alert_info("Testing {.pkg {pkg$package}}")
withr::local_envvar(r_env_vars())
testthat::test_local(pkg$path, filter = filter, stop_on_failure = stop_on_failure,
...)
}
<bytecode: 0x000000009e53be20>
<environment: namespace:devtools>Chi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Tissue = as.character(paste("Crop")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Crop=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Hindgut
tmp = subset(tab_Hisstab_rev , Tissue%in%c("Hindgut"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_Hisstab_rev' introuvablemod.gen = fitme((RFP.Dapi) ~ Day * Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((RFP.Dapi) ~ Day * Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme((RFP.Dapi) ~ Day + Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvabletestfunction (pkg = ".", filter = NULL, stop_on_failure = FALSE,
export_all = TRUE, ...)
{
save_all()
pkg <- as.package(pkg)
if (!uses_testthat(pkg) && interactive()) {
cli::cli_alert_danger("No testing infrastructure found. Create it?")
if (utils::menu(c("Yes", "No")) == 1) {
usethis_use_testthat(pkg)
}
return(invisible())
}
load_all(pkg$path)
cli::cli_alert_info("Testing {.pkg {pkg$package}}")
withr::local_envvar(r_env_vars())
testthat::test_local(pkg$path, filter = filter, stop_on_failure = stop_on_failure,
...)
}
<bytecode: 0x000000009e53be20>
<environment: namespace:devtools>Chi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Tissue = as.character(paste("Hindgut")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Hindgut=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Table
tab_stat=rbind(tab_stat_Crop,tab_stat_Hindgut)Error in eval(quote(list(...)), env): objet 'tab_stat_Crop' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("(RFP/Dapi) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Variable", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_Hisstab=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_rev_Hisstab$Diet = "HY"Error in tab_stat_rev_Hisstab$Diet = "HY": objet 'tab_stat_rev_Hisstab' introuvableSample_size=
tab_Hisstab_rev%>%
group_by(Diet, Day, Tissue)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Day, Tissue): objet 'tab_Hisstab_rev' introuvable### Plot
Limits = c("0","14")
Plot_Fig4S2B=
ggplot(tab_Hisstab_rev, aes(x = Day, y = RFP.Dapi))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 4) +
facet_grid(Tissue ~ Diet,labeller=label_parsed)+
geom_text(data = Sample_size, mapping = aes(x = Day, y = 10, label = paste("(",Sample_size,")",sep="")),size=3)+
scale_fill_manual(limits=c("HS","HY"),
values=c("#FFB4B4","#C3E6FC"))+
scale_x_discrete("Day of dissection post RU486 pulse",
limits=Limits,
labels=c("0","14"))+
scale_y_continuous(expression(paste("RFP pos. cells / Total cells %")),
limits=c(0,110),
breaks=seq(0,100,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black", margin = margin(t = 0, r = 0, b = 0, l = 0) ),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text = element_text(size =Smallfont-2, colour = "black",face="italic", margin = margin(t = 2, r = 1, b = 2, l = 1)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_Hisstab_rev, aes(x = Day, y = RFP.Dapi)): objet 'tab_Hisstab_rev' introuvablePlot_Fig4S2BError in eval(expr, envir, enclos): objet 'Plot_Fig4S2B' introuvableCell loss assay performed at 5 days post start of chase shows limited cell loss in HY to HY condition. Number of ECs in the posterior midgut, both marked (Red, old ECs) and unmarked (Blue, new ECs) by RFP, error bars are SE from 3 repeats.
tab_prop_cell_RFP_kin =
d[["4S2C"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
mutate(Post.Dapi.Number = (Post.Dapi.Number)*2)%>%
mutate(Post.RFP.Number = (Post.RFP.Number)*2)%>%
mutate(Post.NonRFP.Number = (Post.Dapi.Number - Post.RFP.Number))%>%
group_by(Day, Diet, CG, Experiment)%>%
summarise(mean_RFP_positive=mean(Post.RFP.Number,na.rm=T),
se_RFP_positive=se(Post.RFP.Number),
mean_RFP_negative=mean(Post.NonRFP.Number,na.rm=T),
se_RFP_negative=se(Post.NonRFP.Number))%>%
mutate(group=paste(Diet,Experiment,sep="_"))%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"attach(tab_prop_cell_RFP_kin)Error in attach(tab_prop_cell_RFP_kin): objet 'tab_prop_cell_RFP_kin' introuvablefor (i in 1:length(Experiment)){
tab_prop_cell_RFP_kin$se_proportionGraphPlus_pos[i] = mean_RFP_positive[i]+se_RFP_positive[i]
tab_prop_cell_RFP_kin$se_proportionGraphMinus_pos[i] = mean_RFP_positive[i]-se_RFP_positive[i]
tab_prop_cell_RFP_kin$se_proportionGraphPlus_neg[i] = mean_RFP_positive[i]+mean_RFP_negative[i]+se_RFP_negative[i]
tab_prop_cell_RFP_kin$se_proportionGraphMinus_neg[i] = mean_RFP_positive[i]+mean_RFP_negative[i]-se_RFP_negative[i]
}Error in eval(expr, envir, enclos): objet 'Experiment' introuvabletmp1 = tab_prop_cell_RFP_kin[,c("Day", "Diet", "CG", "Experiment","mean_RFP_positive", "se_RFP_positive","se_proportionGraphPlus_pos", "se_proportionGraphMinus_pos")]Error in eval(expr, envir, enclos): objet 'tab_prop_cell_RFP_kin' introuvabletmp1$RFP="Positive"Error in tmp1$RFP = "Positive": objet 'tmp1' introuvabletmp1=dplyr::rename(tmp1,mean_RFP = mean_RFP_positive,
se_RFP = se_RFP_positive,
se_proportionGraphPlus =se_proportionGraphPlus_pos,
se_proportionGraphMinus= se_proportionGraphMinus_pos)Error in dplyr::rename(tmp1, mean_RFP = mean_RFP_positive, se_RFP = se_RFP_positive, : objet 'tmp1' introuvabletmp2 = tab_prop_cell_RFP_kin[,c("Day", "Diet", "CG", "Experiment","mean_RFP_negative", "se_RFP_negative", "se_proportionGraphMinus_neg" ,"se_proportionGraphPlus_neg")]Error in eval(expr, envir, enclos): objet 'tab_prop_cell_RFP_kin' introuvabletmp2$RFP="Negative"Error in tmp2$RFP = "Negative": objet 'tmp2' introuvabletmp2=dplyr::rename(tmp2,mean_RFP = mean_RFP_negative,
se_RFP = se_RFP_negative,
se_proportionGraphPlus =se_proportionGraphPlus_neg,
se_proportionGraphMinus= se_proportionGraphMinus_neg)Error in dplyr::rename(tmp2, mean_RFP = mean_RFP_negative, se_RFP = se_RFP_negative, : objet 'tmp2' introuvabletab_prop_cell_RFP_kin = rbind(tmp1,tmp2)Error in eval(quote(list(...)), env): objet 'tmp1' introuvabletab_prop_cell_RFP_kin =
tab_prop_cell_RFP_kin%>%
mutate_if(is.numeric,round,0)%>%
mutate_if(is.character,as.factor)Error in is_grouped_df(tbl): objet 'tab_prop_cell_RFP_kin' introuvablelevels(tab_prop_cell_RFP_kin$Diet) <- c("HS", "HS to HS" , "HS to HY", "HY", "HY to HS", "HY to HY")Error in levels(tab_prop_cell_RFP_kin$Diet) <- c("HS", "HS to HS", "HS to HY", : objet 'tab_prop_cell_RFP_kin' introuvableSample_size=
d[["4S2C"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size$Experiment = c("G", "G", "G", "S", "S", "S")Error in Sample_size$Experiment = c("G", "G", "G", "S", "S", "S"): objet 'Sample_size' introuvablelevels(Sample_size$Diet) <- c("HS", "HS to HS" , "HS to HY", "HY", "HY to HS", "HY to HY")Error in levels(Sample_size$Diet) <- c("HS", "HS to HS", "HS to HY", "HY", : objet 'Sample_size' introuvablePlot_Fig4S2C =
ggplot(tab_prop_cell_RFP_kin, aes(x=Diet, y=mean_RFP))+
geom_bar(stat="identity",aes(fill=RFP),color="black",width=.90)+
geom_errorbar(aes(ymin= se_proportionGraphMinus, ymax= se_proportionGraphPlus),width=0.25)+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 200, label = paste("(",Sample_size,")",sep="")),size=3)+
#facet_wrap(.~Experiment,scales="free_x")+
scale_fill_manual(name = "RFP labelling",
values=c("#3a5ecc","#cc0000"),
labels = c("Negative", "Positive"))+
scale_y_continuous("Number of cells (mean \u00B1se)",
limits=c(0,5800),
breaks=seq(0,5000,by=500))+
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = c(0.2,0.87),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
strip.text = element_blank())Error in ggplot(tab_prop_cell_RFP_kin, aes(x = Diet, y = mean_RFP)): objet 'tab_prop_cell_RFP_kin' introuvable #strip.background = element_rect(fill=NA, colour="black"),
#strip.placement="outside")
Plot_Fig4S2CError in eval(expr, envir, enclos): objet 'Plot_Fig4S2C' introuvableDiet composition modulates cell replacement rate (cell/day). Bar chart was made using the same data as in Figure 4 K, L.
tab_relative_cell_rate_supp =
d[["4L, 4S2D"]]%>%
select(-starts_with("X"))%>%
drop_na()%>%
mutate_if(is.character,as.factor)%>%
group_by(Diet1, Experiment, Experiment2, GL)%>%
summarise(mean_Daily=mean(Daily,na.rm=T))%>%
mutate(group=paste(Diet1,Experiment,sep="_"))%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'select' applicable pour un objet de classe "NULL"tab_relative_cell_rate_ratio =
tab_relative_cell_rate_supp%>%
group_by(Diet1,Experiment2)%>%
summarize(Ratio = round(mean_Daily[GL == "Gain"] / (-mean_Daily[GL == "Loss"]),2))%>%
mutate(GL="Loss")Error in group_by(., Diet1, Experiment2): objet 'tab_relative_cell_rate_supp' introuvablelevels(tab_relative_cell_rate_supp$Diet1) <- c("HS to HS" , "HS to HY", "HY to HS", "HY to HY")Error in levels(tab_relative_cell_rate_supp$Diet1) <- c("HS to HS", "HS to HY", : objet 'tab_relative_cell_rate_supp' introuvablelevels(tab_relative_cell_rate_ratio$Diet1) <- c("HS to HS" , "HS to HY", "HY to HS", "HY to HY")Error in levels(tab_relative_cell_rate_ratio$Diet1) <- c("HS to HS", "HS to HY", : objet 'tab_relative_cell_rate_ratio' introuvablePlot_Fig4S2D =
ggplot(tab_relative_cell_rate_supp, aes(x = Diet1, y = mean_Daily, fill = GL))+
geom_bar(stat="identity",aes(fill=GL),color="black",width=.90)+
geom_hline(yintercept = 0)+
geom_text(data=tab_relative_cell_rate_ratio,mapping=aes(x=Diet1,y=-20,label=Ratio), color = "red")+
facet_grid(.~Experiment2,scales="free_x")+
scale_fill_manual(name = "Enterocyte",
values=c("palegreen", "moccasin"),
labels = c("Gain", "Loss"))+
scale_y_continuous("Cell rate (cell/ day)",
limits=c(-220,220),
breaks=seq(-200,200,by=50))+
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = c(0.18,0.88),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_relative_cell_rate_supp, aes(x = Diet1, y = mean_Daily, : objet 'tab_relative_cell_rate_supp' introuvablePlot_Fig4S2DError in eval(expr, envir, enclos): objet 'Plot_Fig4S2D' introuvable##Export Figure 4S2
Diet influences midgut transcriptomes after an initial programmed developmental transition. The plot shows a PCA of the whole transcriptome, with means per diet per day ± standard error (3 repeats). Numbers on the plot represent the day of dissection from eclosion. Lines connect the datapoints sequentially (Day 0 to day 1, day 1 to day 2, and so on), and show the divergent transcriptomic trajectory followed by midguts on the two different diets from eclosion.
dataInd =
d[["gutGrowthDataIndex"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL" #add string to direct to enumerated reads
dataInd$countFile = gsub(".fastq", "_sn.sam.count", dataInd$library)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'gsub' : objet 'dataInd' introuvabledataInd$samp = paste("day",dataInd$day,"_diet",dataInd$diet,"_rep",dataInd$rep,sep="")Error in eval(quote(list(...)), env): objet 'dataInd' introuvabledataInd$expCond = factor(paste(dataInd$day, dataInd$diet, sep=""))Error in eval(quote(list(...)), env): objet 'dataInd' introuvabledataInd$dietCol = with( dataInd, ifelse(diet=="x", "#ff9595", ifelse(diet=="y", "#abefff", "#67ff67")) )Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'data' lors de la s�lection d'une m�thode pour la fonction 'with' : objet 'dataInd' introuvabletab_read_RNAseq = d[["readTable"]]
geneID = rownames(tab_read_RNAseq) = tab_read_RNAseq$FBid
tab_read_RNAseq = tab_read_RNAseq[,2:ncol(tab_read_RNAseq)]Error in 2:ncol(tab_read_RNAseq): l'argument est de longueur nullenormCounts = d[["normCounts"]]
rownames(normCounts) = geneID
normCounts = normCounts[,2:ncol(normCounts)]Error in 2:ncol(normCounts): l'argument est de longueur nulle #pca without day 4
dataInd2 = droplevels(subset(dataInd, day!=4))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'dataInd' introuvablenormCounts2 = normCounts[,dataInd$day!=4]Error in eval(expr, envir, enclos): objet 'dataInd' introuvablepca2 = prcomp(t(normCounts2)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 't' : objet 'normCounts2' introuvablesummary(pca2)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'summary' : objet 'pca2' introuvable #calculate means and SEs of the PCs
#without day 4
pcMns = aggregate(pca2$x ~ day * diet + dietCol, data=dataInd2, mean)Error in eval(m$data, parent.frame()): objet 'dataInd2' introuvablepcSEs = aggregate(pca2$x ~ day * diet + dietCol, data=dataInd2, function(x){sd(x)/sqrt(length(x))})Error in eval(m$data, parent.frame()): objet 'dataInd2' introuvablepcMns = droplevels(subset(pcMns, day!=4))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'pcMns' introuvablepcSEs = droplevels(subset(pcSEs, day!=4))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'droplevels' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'pcSEs' introuvablepcMns = pcMns[order(pcMns$day),]Error in eval(expr, envir, enclos): objet 'pcMns' introuvablepcSEs = pcSEs[order(pcSEs$day),]Error in eval(expr, envir, enclos): objet 'pcSEs' introuvablepcMns = pcMns%>%
mutate_if(is.character,as.factor)%>%
select(day,diet,dietCol,PC1,PC2)%>%
as.data.frame()%>%
dplyr::rename(PC1_mean=PC1,
PC2_mean=PC2)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'pcMns' introuvablepcSEs = pcSEs%>%
mutate_if(is.character,as.factor)%>%
select(day,diet,dietCol,PC1,PC2)%>%
dplyr::rename(PC1_se=PC1,
PC2_se=PC2)Error in is_grouped_df(tbl): objet 'pcSEs' introuvabletab_PCA = left_join(pcMns,pcSEs)Error in left_join(pcMns, pcSEs): objet 'pcMns' introuvabletab_PCA$diet1 =ifelse(tab_PCA$diet=="x","#ff9595","#abefff")Error in ifelse(tab_PCA$diet == "x", "#ff9595", "#abefff"): objet 'tab_PCA' introuvabletab_PCA$diet1[1]="#ff9595"Error in tab_PCA$diet1[1] = "#ff9595": objet 'tab_PCA' introuvabletab_PCA$diet2=ifelse(tab_PCA$diet=="y","#abefff","#ff9595")Error in ifelse(tab_PCA$diet == "y", "#abefff", "#ff9595"): objet 'tab_PCA' introuvabletab_PCA$diet2[1]="#abefff"Error in tab_PCA$diet2[1] = "#abefff": objet 'tab_PCA' introuvabletab_PCA=mutate_if(tab_PCA,is.character,as.factor)Error in is_grouped_df(tbl): objet 'tab_PCA' introuvabletab_PCA$diet1= factor(tab_PCA$diet1,levels=c("#67ff67","#abefff","#ff9595"))Error in factor(tab_PCA$diet1, levels = c("#67ff67", "#abefff", "#ff9595")): objet 'tab_PCA' introuvabletab_PCA$diet2= factor(tab_PCA$diet2,levels=c("#67ff67","#abefff","#ff9595"))Error in factor(tab_PCA$diet2, levels = c("#67ff67", "#abefff", "#ff9595")): objet 'tab_PCA' introuvablePlot_Fig5A=
ggplot(tab_PCA,aes(x=PC1_mean, y=PC2_mean))+
geom_point(aes(color=dietCol),size=2 ,shape=19)+
geom_errorbarh(aes(xmax = PC1_mean+PC1_se, xmin =PC1_mean-PC1_se,color=dietCol ),height=0.1)+
geom_errorbar(aes(ymax = PC2_mean+PC2_se, ymin =PC2_mean-PC2_se,color=dietCol ),width =0.1)+
geom_path(size=0.8,aes(group=diet1,color=diet1))+
geom_path(size=0.8,aes(group=diet2,color=diet2))+
geom_text(aes(label=day),size=4,vjust = 0, nudge_y = -2.5)+
scale_color_manual(values=c("#67ff67","#abefff","#ff9595"))+
scale_x_continuous(paste("PC1 (", round(summary(pca2)$importance[2,1]*100), "%)", sep=""),
limits=c(-50,60),
breaks=seq(-50,60,by=20))+
scale_y_continuous(paste("PC2 (", round(summary(pca2)$importance[2,2]*100), "%)", sep=""),
limits=c(-30,45),
breaks=seq(-30,40,by=10))+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_PCA, aes(x = PC1_mean, y = PC2_mean)): objet 'tab_PCA' introuvablePlot_Fig5AError in eval(expr, envir, enclos): objet 'Plot_Fig5A' introuvableDiet modulates expression of functionally distinct gene classes. Midguts of flies fed HY diet show higher expression of genes with digestive functions, while HS diet involves mainly genes attributed to stress response and growth. X-axis represents the statistical significance of the gene ontology (GO) categories (y-axis) after adjustment for multiple testing. Size of the dot is proportional to number of genes in the given GO category
tab_GO_results =
d[["5B"]]%>%
mutate_if(is.character,as.factor)%>%
mutate(Padj=-log(p.value,10),
Term = str_to_sentence(Term))%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"tab_GO_results$Term <- factor(tab_GO_results$Term, levels = tab_GO_results$Term[order(tab_GO_results$Diet, tab_GO_results$Padj, tab_GO_results$Significant)])Error in factor(tab_GO_results$Term, levels = tab_GO_results$Term[order(tab_GO_results$Diet, : objet 'tab_GO_results' introuvable#order GO categories based on size of Padj
tab_GO_results$Diet <- factor(tab_GO_results$Diet, levels = c("HY", "HS"))Error in factor(tab_GO_results$Diet, levels = c("HY", "HS")): objet 'tab_GO_results' introuvable### Plot
Plot_Fig5B=
ggplot(tab_GO_results, aes(x = Padj, y = Term))+
geom_point(aes(size=Significant,fill=Diet),shape=21) +
facet_grid(Diet~.,scales="free_y",space="free")+
scale_fill_manual(limits=c("HS","HY"),
values=c("#FFB4B4","#C3E6FC"))+
geom_vline(xintercept = 1.3,linetype=3)+
scale_y_discrete("GO categories")+
scale_x_continuous(expression(paste("-P-value adjusted (", log[10],")")),
limits=c(0,31),
breaks=c(0,seq(10,30,by=10)))+
scale_size_continuous("Nbr genes", range =c(1,5) )+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont-2,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = "top",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.margin=margin(b=0, unit='cm'),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont-2),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 3, r = 1, b = 3, l = 1)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")+
guides(fill=F)Error in ggplot(tab_GO_results, aes(x = Padj, y = Term)): objet 'tab_GO_results' introuvablePlot_Fig5BError in eval(expr, envir, enclos): objet 'Plot_Fig5B' introuvableTable of genes significantly differently expressed, between HS and HY, as a ratio of HS/HY, representing midgut response to HS and HY diets; additional information on the statistics is found in material and methods; asterisks denote genes significantly different for p-value but not for adjusted p-value
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5C.jpg") Error in transpose(y): object is NULLgob_imageFig5C = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5C)Error in grid.draw(gob_imageFig5C): objet 'gob_imageFig5C' introuvableCell proliferation is possible on HS diet when genetically induced. Progenitor-specific (EsgTS) overexpression of a constitutively active form of Ras (UAS-RasV12) and of UAS-Tor-DER (EGFR Active), both known proliferative inducers, allows for increased proliferation on HS diet. P-values on top of the chart refer to comparison vs control, P-values at the bottom refer to comparison between HS and HY for each sample. Complete statistical annotation on image can be fund in the manuscript’s figures.
Tab_Ras_PH3_Rev =
d[["5D"]]%>%
mutate_at(vars(ends_with(".L")),~./1000)%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(PH3_positive_cell=Total.PH3,
Diet=Treatment,
Male_Line=Male.Line)%>%
mutate(Cross=fct_relevel(Cross,"EsgTsXControl","EsgTsX64195", "EsgTsXTorDER" ))Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"###Stats
##Control
tmp = subset(Tab_Ras_PH3_Rev , Male_Line%in%c("Control"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Tab_Ras_PH3_Rev' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY Control")),
Rep = nlevels(Tab_Ras_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_Ras_PH3_Rev' introuvabletab_stat_Control=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable##Ras85DV12 (64195)
tmp = subset(Tab_Ras_PH3_Rev , Male_Line%in%c("Ras85DV12"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Tab_Ras_PH3_Rev' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY Ras85DV12")),
Rep = nlevels(Tab_Ras_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_Ras_PH3_Rev' introuvabletab_stat_Ras85DV12=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable##Ras85DV12_2 (TorDER)
tmp = subset(Tab_Ras_PH3_Rev , Male_Line%in%c("TorDER"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Tab_Ras_PH3_Rev' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY TorDER")),
Rep = nlevels(Tab_Ras_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_Ras_PH3_Rev' introuvabletab_stat_TorDER=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_Control, tab_stat_Ras85DV12, tab_stat_TorDER)Error in eval(quote(list(...)), env): objet 'tab_stat_Control' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Diet + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_RasPH3=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_rev_RasPH3$Male_Line= tab_stat_rev_RasPH3$VariableError in eval(expr, envir, enclos): objet 'tab_stat_rev_RasPH3' introuvable###Stats HS vs control
tmpd = subset(Tab_Ras_PH3_Rev , Diet%in%c("HS"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Tab_Ras_PH3_Rev' introuvable##Ras85DV12
tmp = subset(tmpd , Male_Line%in%c("Control", "Ras85DV12"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme((PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme((PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS Ras85DV12 vs HS Control")),
Rep = nlevels(Tab_Ras_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_Ras_PH3_Rev' introuvabletab_stat_HS_Ras85DV12=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable##TorDER
tmp = subset(tmpd , Male_Line%in%c("Control", "TorDER"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS TorDER vs HS Control")),
Rep = nlevels(Tab_Ras_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_Ras_PH3_Rev' introuvabletab_stat_HS_TorDER=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Table
tab_stat=rbind(tab_stat_HS_Ras85DV12, tab_stat_HS_TorDER)Error in eval(quote(list(...)), env): objet 'tab_stat_HS_Ras85DV12' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_RasPH3_HS=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_rev_RasPH3_HS$Male_Line= tab_stat_rev_RasPH3_HS$VariableError in eval(expr, envir, enclos): objet 'tab_stat_rev_RasPH3_HS' introuvable###Stats HY vs control
tmpd = subset(Tab_Ras_PH3_Rev , Diet%in%c("HY"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'Tab_Ras_PH3_Rev' introuvable##Ras85DV12
tmp = subset(tmpd , Male_Line%in%c("Control", "Ras85DV12"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme((PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest((PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme((PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HY Ras85DV12 vs HY Control")),
Rep = nlevels(Tab_Ras_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_Ras_PH3_Rev' introuvabletab_stat_HY_Ras85DV12=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable##TorDER
tmp = subset(tmpd , Male_Line%in%c("Control", "TorDER"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HY TorDER vs HY Control")),
Rep = nlevels(Tab_Ras_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Tab_Ras_PH3_Rev' introuvabletab_stat_HY_TorDER=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Table
tab_stat=rbind(tab_stat_HY_Ras85DV12, tab_stat_HY_TorDER)Error in eval(quote(list(...)), env): objet 'tab_stat_HY_Ras85DV12' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_RasPH3_HY=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_rev_RasPH3_HY$Male_Line= tab_stat_rev_RasPH3_HY$VariableError in eval(expr, envir, enclos): objet 'tab_stat_rev_RasPH3_HY' introuvable#Samplesize
Sample_size=
Tab_Ras_PH3_Rev%>%
group_by(Male_Line,Diet)%>%
summarise(Sample_size=n())Error in group_by(., Male_Line, Diet): objet 'Tab_Ras_PH3_Rev' introuvable### Plot
Tab_Ras_PH3_Rev$Male_Line = factor(Tab_Ras_PH3_Rev$Male_Line, labels = c(expression(italic(paste("Control"))), expression(italic(paste("Ra",s^{V12},sep=""))), expression(italic(paste("Tor-DER")))))Error in factor(Tab_Ras_PH3_Rev$Male_Line, labels = c(expression(italic(paste("Control"))), : objet 'Tab_Ras_PH3_Rev' introuvableSample_size$Male_Line = factor(Sample_size$Male_Line, labels = c(expression(italic(paste("Control"))), expression(italic(paste("Ra",s^{V12},sep=""))), expression(italic(paste("Tor-DER")))))Error in factor(Sample_size$Male_Line, labels = c(expression(italic(paste("Control"))), : objet 'Sample_size' introuvabletab_stat_rev_RasPH3$Male_Line = factor(tab_stat_rev_RasPH3$Male_Line, labels = c(expression(italic(paste("Control"))), expression(italic(paste("Ra",s^{V12},sep=""))), expression(italic(paste("Tor-DER")))))Error in factor(tab_stat_rev_RasPH3$Male_Line, labels = c(expression(italic(paste("Control"))), : objet 'tab_stat_rev_RasPH3' introuvabletab_stat_rev_RasPH3_HS$Male_Line = factor(tab_stat_rev_RasPH3_HS$Male_Line, labels = c(expression(italic(paste("Ra",s^{V12},sep=""))), expression(italic(paste("Tor-DER")))))Error in factor(tab_stat_rev_RasPH3_HS$Male_Line, labels = c(expression(italic(paste("Ra", : objet 'tab_stat_rev_RasPH3_HS' introuvabletab_stat_rev_RasPH3_HY$Male_Line = factor(tab_stat_rev_RasPH3_HY$Male_Line, labels = c(expression(italic(paste("Ra",s^{V12},sep=""))), expression(italic(paste("Tor-DER")))))Error in factor(tab_stat_rev_RasPH3_HY$Male_Line, labels = c(expression(italic(paste("Ra", : objet 'tab_stat_rev_RasPH3_HY' introuvable#Annotation in the plot
ann_textHS <-data.frame(Male_Line = "Control", anot = "Vs Ctrl HS")
ann_textHS$Male_Line = factor(ann_textHS$Male_Line, labels = c(expression(italic(paste("Control")))))
ann_textHY <-data.frame(Male_Line = "Control", anot = "Vs Ctrl HY")
ann_textHY$Male_Line = factor(ann_textHY$Male_Line, labels = c(expression(italic(paste("Control")))))
ann_text <-data.frame(Male_Line = "Ras85DV12", anot = "HS vs HY")
ann_text$Male_Line = factor(ann_text$Male_Line, labels = c(expression(italic(paste("Ra",s^{V12},sep="")))))
#Plot
Limits = c("HS","HY")
Plot_Fig5D=
ggplot(Tab_Ras_PH3_Rev, aes(x = Diet, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 3) +
facet_grid(. ~ Male_Line,labeller=label_parsed)+
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -10, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat_rev_RasPH3, aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 105), textsize = 2.5, vjust = -0.2, manual = TRUE)+
scale_fill_manual(limits=c("HS","HY"),
values=c("#FFB4B4","#C3E6FC"))+
scale_x_discrete("",
limits=Limits,
labels=c("HS","HY"))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-15,175),
breaks=seq(0,110,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black", margin = margin(t = 0, r = 0, b = 0, l = 0) ),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text = element_text(size =Smallfont-2, colour = "black",face="italic", margin = margin(t = 2, r = 1, b = 2, l = 1)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Tab_Ras_PH3_Rev, aes(x = Diet, y = PH3_positive_cell)): objet 'Tab_Ras_PH3_Rev' introuvablePlot_Fig5DError in eval(expr, envir, enclos): objet 'Plot_Fig5D' introuvableEnterocyte specific over expression (MyoTS) of UAS-upd3-OE and UAS-spi-SEC elicit increased proliferation, strongly only on HY diet, and weakly on HS with UAS-upd3-OE. P-values on top of the chart refer to comparisons with the control, p-values at the bottom refer to comparison between HS and HY for each sample. Flies were 9 days old when dissected. Complete statistical annotation on image can be fund in the manuscript’s figures.
tab_Myo_PH3_Rev =
d[["5E"]]%>%
mutate_at(vars(ends_with(".L")),~./1000)%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(PH3_positive_cell=Total.PH3,
Diet=Treatment,
Male_Line=Male.Line)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"###Stats HS vs HY
##Control
tmp = subset(tab_Myo_PH3_Rev, Male_Line%in%c("Control"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_Myo_PH3_Rev' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Control HS vs HY")),
Rep = nlevels(tab_Myo_PH3_Rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_Myo_PH3_Rev' introuvabletab_stat_Control=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_Control$Male_Line = "Control"Error in tab_stat_Control$Male_Line = "Control": objet 'tab_stat_Control' introuvable##spi-sec
tmp = subset(tab_Myo_PH3_Rev , Male_Line%in%c("spi-SEC"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_Myo_PH3_Rev' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("spi-SEC HS vs HY")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_spi_sec=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_spi_sec$Male_Line = "spi-SEC"Error in tab_stat_spi_sec$Male_Line = "spi-SEC": objet 'tab_stat_spi_sec' introuvable##upd3-OE
tmp = subset(tab_Myo_PH3_Rev , Male_Line%in%c("upd3-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_Myo_PH3_Rev' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Diet + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Diet + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("upd3-OE HS vs HY")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_upd3_OE=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_upd3_OE$Male_Line = "upd3-OE"Error in tab_stat_upd3_OE$Male_Line = "upd3-OE": objet 'tab_stat_upd3_OE' introuvabletab_stat=rbind(tab_stat_Control,tab_stat_spi_sec, tab_stat_upd3_OE)Error in eval(quote(list(...)), env): objet 'tab_stat_Control' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value", "Genotype Male_line" ,"p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Diet + (1 | Repeat)" = 10))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_MyoPH3=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable###Stats HS vs control
tmpd = subset(tab_Myo_PH3_Rev , Diet%in%c("HS"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_Myo_PH3_Rev' introuvable##spi-sec
tmp = subset(tmpd , Male_Line%in%c("Control", "spi-SEC"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Control vs spi-SEC (HS)")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_HS_spi_sec=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_HS_spi_sec$Male_Line = "spi-SEC"Error in tab_stat_HS_spi_sec$Male_Line = "spi-SEC": objet 'tab_stat_HS_spi_sec' introuvable##upd3-OE
tmp = subset(tmpd , Male_Line%in%c("Control", "upd3-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Control vs upd3-OE (HS)")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_HS_upd3_OE=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_HS_upd3_OE$Male_Line = "upd3-OE"Error in tab_stat_HS_upd3_OE$Male_Line = "upd3-OE": objet 'tab_stat_HS_upd3_OE' introuvable#Table
tab_stat=rbind(tab_stat_HS_spi_sec, tab_stat_HS_upd3_OE)Error in eval(quote(list(...)), env): objet 'tab_stat_HS_spi_sec' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Genotype Male_Line" ,"p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Genotype + (1 | Repeat)" = 10))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_MyoPH3_HS=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable###Stats HY vs control
tmpd = subset(tab_Myo_PH3_Rev , Diet%in%c("HY"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_Myo_PH3_Rev' introuvable##spi-sec
tmp = subset(tmpd , Male_Line%in%c("Control", "spi-SEC"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Control vs spi-SEC (HY)")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_HY_spi_sec=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_HY_spi_sec$Male_Line = "spi-SEC"Error in tab_stat_HY_spi_sec$Male_Line = "spi-SEC": objet 'tab_stat_HY_spi_sec' introuvable##upd3-OE
tmp = subset(tmpd , Male_Line%in%c("Control", "upd3-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tmpd' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Control vs upd3-OE (HY)")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_HY_upd3_OE=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_HY_upd3_OE$Male_Line = "upd3-OE"Error in tab_stat_HY_upd3_OE$Male_Line = "upd3-OE": objet 'tab_stat_HY_upd3_OE' introuvable#Table
tab_stat=rbind(tab_stat_HY_spi_sec, tab_stat_HY_upd3_OE)Error in eval(quote(list(...)), env): objet 'tab_stat_HY_spi_sec' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value", "Genotype Male_Line" ,"p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Genotype + (1 | Repeat)" = 10))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_MyoPH3_HY=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvableSample_size=
tab_Myo_PH3_Rev%>%
group_by(Male_Line,Diet)%>%
summarise(Sample_size=n())Error in group_by(., Male_Line, Diet): objet 'tab_Myo_PH3_Rev' introuvable#Annotation in the plot
ann_textHS <-data.frame(Male_Line = "Control", anot = "Vs Ctrl HS")
ann_textHY <-data.frame(Male_Line = "Control", anot = "Vs Ctrl HY")
ann_text <-data.frame(Male_Line = "spi-SEC", anot = "HS vs HY")
### Plot
Limits = c("HS","HY")
Plot_Fig5E=
ggplot(tab_Myo_PH3_Rev, aes(x = Diet, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 3) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -10, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat_rev_MyoPH3, aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 135), textsize = 2.5, vjust = -0.2, manual = TRUE)+
facet_grid(. ~ Male_Line)+
scale_fill_manual(limits=c("HS","HY"),
values=c("#FFB4B4","#C3E6FC"))+
scale_x_discrete("",
limits=Limits,
labels=c("HS","HY"))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-15,225),
breaks=seq(0,130,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black", margin = margin(t = 0, r = 0, b = 0, l = 0) ),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = xSmallfont, colour = "black", angle=0, face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = xSmallfont, colour = "black", angle=0, face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_Myo_PH3_Rev, aes(x = Diet, y = PH3_positive_cell)): objet 'tab_Myo_PH3_Rev' introuvablePlot_Fig5EError in eval(expr, envir, enclos): objet 'Plot_Fig5E' introuvableGeneral translation is lower on HS than HY, shown by puromycin incorporation assay. Images show lower incorporation on HS (F, F’, top row) than HY (G, G’, bottom row) in region 4 of the midgut.Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5F.jpg") Error in transpose(y): object is NULLgob_imageFig5F = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5F)Error in grid.draw(gob_imageFig5F): objet 'gob_imageFig5F' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5F'.jpg") Error in transpose(y): object is NULLgob_imageFig5F2 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5F2)Error in grid.draw(gob_imageFig5F2): objet 'gob_imageFig5F2' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5G.jpg") Error in transpose(y): object is NULLgob_imageFig5G = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5G)Error in grid.draw(gob_imageFig5G): objet 'gob_imageFig5G' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5G'.jpg") Error in transpose(y): object is NULLgob_imageFig5G2 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5G2)Error in grid.draw(gob_imageFig5G2): objet 'gob_imageFig5G2' introuvableQuantification of mean pixel intensity of puromycin stain.
Length_Puromycin =
d[["5H"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(Puromycin_int=Mean)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_Puromycin%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'Length_Puromycin' introuvable###Stats
mod.gen = fitme(log(Puromycin_int) ~ Diet + (1 | Repeat),data = Length_Puromycin)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_Puromycin' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Puromycin_int) ~ Diet + (1 / Repeat),data = Length_Puromycin)Error in is.data.frame(data): objet 'Length_Puromycin' introuvablemod.gen1 = fitme(log(Puromycin_int) ~ 1 + (1 | Repeat),data = Length_Puromycin)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_Puromycin' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(Length_Puromycin$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_Puromycin' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Puromycin intensity) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
Plot_Fig5H=
ggplot(Length_Puromycin, aes(x = Diet, y = Puromycin_int))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 1) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 1, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 47, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=c("HS","HY"),
values=c("#FFB4B4","#C3E6FC"))+
scale_x_discrete("",
limits=c("HS","HY"),
labels=c("HS","HY"))+
scale_y_continuous("Mean pixel intensity
puromycin (a.u.)",
limits=c(0,50),
breaks=seq(0,40,by=10))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text = element_text(size =Smallfont-2, colour = "black",face="italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_Puromycin, aes(x = Diet, y = Puromycin_int)): objet 'Length_Puromycin' introuvablePlot_Fig5HError in eval(expr, envir, enclos): objet 'Plot_Fig5H' introuvablep-eIF2α stain is elevated on HS (I, I’, top row) compared to HY (J, J’, bottom row). Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5I.jpg") Error in transpose(y): object is NULLgob_imageFig5I = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5I)Error in grid.draw(gob_imageFig5I): objet 'gob_imageFig5I' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5I'.jpg") Error in transpose(y): object is NULLgob_imageFig5I2 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5I2)Error in grid.draw(gob_imageFig5I2): objet 'gob_imageFig5I2' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5J.jpg") Error in transpose(y): object is NULLgob_imageFig5J = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5J)Error in grid.draw(gob_imageFig5J): objet 'gob_imageFig5J' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5J'.jpg") Error in transpose(y): object is NULLgob_imageFig5J2 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5J2)Error in grid.draw(gob_imageFig5J2): objet 'gob_imageFig5J2' introuvableQuantification of mean pixel intensity of p-eIF2α stain.
Length_EIF2 =
d[["5K"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(EIF2_int=Mean)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
Length_EIF2%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'Length_EIF2' introuvable###Stats
mod.gen = fitme(log(EIF2_int) ~ Diet + (1 | Repeat),data = Length_EIF2)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_EIF2' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(EIF2_int) ~ Diet + (1 / Repeat),data = Length_EIF2)Error in is.data.frame(data): objet 'Length_EIF2' introuvablemod.gen1 = fitme(log(EIF2_int) ~ 1 + (1 | Repeat),data = Length_EIF2)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'Length_EIF2' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(Length_EIF2$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'Length_EIF2' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(EIF2 intensity) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
Plot_Fig5K=
ggplot(Length_EIF2, aes(x = Diet, y = EIF2_int))+
geom_boxplot(aes(fill = Diet), colour = "black", size = 0.2,outlier.shape = NA) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 3) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 3, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 135, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=c("HS","HY"),
values=c("#FFB4B4","#C3E6FC"))+
scale_x_discrete("",
limits=c("HS","HY"),
labels=c("HS","HY"))+
scale_y_continuous(expression(paste("Mean pixel intensity p-eIF2",alpha," (a.u.)",sep="")),
limits=c(0,140),
breaks=seq(0,125,by=25))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text = element_text(size =Smallfont-2, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(Length_EIF2, aes(x = Diet, y = EIF2_int)): objet 'Length_EIF2' introuvablePlot_Fig5KError in eval(expr, envir, enclos): objet 'Plot_Fig5K' introuvableRe-enabling translation can restore mitosis in midguts shrinking after being shifted from HY to HS diet for 7 days. Blocking translational inhibition with ActTS>Gcn2-IR or ActTS>LK6-IR is sufficient to increase pH3+ cells in midguts of flies on HS diet. However, ActTS>PEK-IR and ActTS>AMPKα-IR had no effect on the number of pH3+ cells. Statistical comparisons are vs control. Full statistical annotation on chart in pubblication
tab_PH3_Translation =
d[["5L"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)%>%
mutate(Male.Line=fct_relevel(Male.Line,c("Control","Ampk-IR","PEK-IR", "Gcn2-IR", "Lk6-IR")))Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_PH3_Translation%>%
group_by(Male.Line)%>%
summarise(Sample_size=n())Error in group_by(., Male.Line): objet 'tab_PH3_Translation' introuvable###Stats
#Gcn2-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","Gcn2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("Gcn2-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_GCN=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#PEK-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","PEK-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("PEK-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_PEK=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Lk6-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","Lk6-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("Lk6-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=5)))Error in levels(x): objet 'tmp' introuvabletab_stat_Lk6=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Ampk-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","Ampk-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("Ampk-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Ampk=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_PEK,tab_stat_Ampk,tab_stat_Lk6,tab_stat_GCN)Error in eval(quote(list(...)), env): objet 'tab_stat_PEK' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =T))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Difference in Diet", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Difference in Diet", "Replicates", "Chi2", : objet 'tab_stat' introuvableletter_position = aggregate(data=tab_PH3_Translation,PH3_positive_cell ~ Male.Line, max)Error in eval(m$data, parent.frame()): objet 'tab_PH3_Translation' introuvabletab_stat=left_join(tab_stat,letter_position)Error in left_join(tab_stat, letter_position): objet 'tab_stat' introuvabletab_stat5L = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_PH3_Translation$Female.Line = factor(tab_PH3_Translation$Female.Line, labels = c(expression(italic(paste("Ac",t^{TS},">",sep="")))))Error in factor(tab_PH3_Translation$Female.Line, labels = c(expression(italic(paste("Ac", : objet 'tab_PH3_Translation' introuvablez=max(tab_PH3_Translation$PH3_positive_cell, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_PH3_Translation' introuvablePlot_Fig5L=
ggplot(tab_PH3_Translation, aes(x = Male.Line, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
geom_text(data = Sample_size, mapping = aes(x = Male.Line, y = -3, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Female.Line, labeller = label_parsed)+
scale_fill_manual(values="#FFB4B4")+
scale_x_discrete("",
limits=c("Control","Ampk-IR","PEK-IR","Gcn2-IR","Lk6-IR"),
labels=c(expression(italic("Control"), italic(paste("AMPK", alpha, "-IR")), italic("PEK-IR"),italic("Gcn2-IR"),italic("Lk6-IR"))))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-3,64),
breaks=seq(0,62,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1, face = "italic"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_PH3_Translation, aes(x = Male.Line, y = PH3_positive_cell)): objet 'tab_PH3_Translation' introuvablePlot_Fig5LError in eval(expr, envir, enclos): objet 'Plot_Fig5L' introuvableDespite increased mitotic activity following repression of translational inhibition in ActTS>Gcn2-IR or ActTS>LK6-IR, midgut size was still reduced on flies kept on HS diet. The statistical comparison is comparing interaction between diet and fly lines. Full statistical annotation on chart in pubblication
tab_length_Translation =
d[["5M"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,c("Control","Gcn2-IR","Lk6-IR")))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_length_Translation%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_length_Translation' introuvable###Stats
#Gcn2-IR
tmp = subset(tab_length_Translation,!is.na(Total_Length_mm) & Male_Line%in%c("Control","Gcn2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_length_Translation' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male_Line = as.character(paste("Gcn2-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_GCN=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#lk6-IR
tmp = subset(tab_length_Translation,!is.na(Total_Length_mm) & Male_Line%in%c("Control","Lk6-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_length_Translation' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male_Line = as.character(paste("Lk6-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_Lk6=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_Lk6,tab_stat_GCN)Error in eval(quote(list(...)), env): objet 'tab_stat_Lk6' introuvabletab_stat$padj = format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Difference in Diet", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Difference in Diet", "Replicates", "Chi2", : objet 'tab_stat' introuvableletter_position = aggregate(data=tab_length_Translation,Total_Length_mm ~ Male_Line, max)Error in eval(m$data, parent.frame()): objet 'tab_length_Translation' introuvabletab_stat=left_join(tab_stat,letter_position)Error in left_join(tab_stat, letter_position): objet 'tab_stat' introuvabletab_stat5M = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_length_Translation$Female_Line = factor(tab_length_Translation$Female_Line, labels = c(expression(italic(paste("Ac",t^{TS},">",sep="")))))Error in factor(tab_length_Translation$Female_Line, labels = c(expression(italic(paste("Ac", : objet 'tab_length_Translation' introuvablez=max(tab_length_Translation$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_length_Translation' introuvablePlot_Fig5M=
ggplot(tab_length_Translation, aes(x = Male_Line, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/50) +
geom_text(data = Sample_size, mapping = aes(x = Male_Line, y = 2.6, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~ Female_Line,labeller=label_parsed )+
scale_fill_manual(values=c("#FFB4B4"))+
scale_x_discrete("",
limits=c("Control","Gcn2-IR", "Lk6-IR"),
labels=c("Control","Gcn2-IR", "Lk6-IR"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2.5,6.1),
breaks=seq(3,6,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1, face = "italic"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_Translation, aes(x = Male_Line, y = Total_Length_mm)): objet 'tab_length_Translation' introuvablePlot_Fig5MError in eval(expr, envir, enclos): objet 'Plot_Fig5M' introuvable##Export Figure 5
Survival assay shows lower survival on HS vs HY. Additional information on the statistics can be found in R markdown. Triangles represent the day when survival was recorded.
tab_survival =
subset(d[["5 - S1A"]],Treatment%in%c("HS","HY"))%>%
mutate(TimeToDeath=as.numeric(TimeToDeath),
Censor=as.numeric(Censor),
Sex="Male")%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction '%in%' : objet 'Treatment' introuvable# analysis
model_Surv= coxme(Surv(TimeToDeath,Censor) ~ Treatment + (1|Repeat) , data= tab_survival)Error in is.data.frame(data): objet 'tab_survival' introuvablemodel_Surv1= coxme(Surv(TimeToDeath,Censor) ~ 1 + (1|Repeat) , data= tab_survival)Error in is.data.frame(data): objet 'tab_survival' introuvabletest = anova(model_Surv1,model_Surv)Error in anova(model_Surv1, model_Surv): objet 'model_Surv1' introuvabletest[2,4] = pchisq(test$Chisq[2],df=1,lower.tail = F)Error in test$Chisq: objet de type 'closure' non indiçabletab_test = data.frame(Variable=c("Full model","(-) Diet"),
logLik=as.numeric(test[,1]),
Chisq=as.numeric(test[,2]),
df=as.numeric(test[,3]),
Pvalue=as.numeric(test[,4]))Error in test[, 1]: objet de type 'closure' non indiçabletab_test%>%
kable(col.names = c("Variable","logLik" ,"Chi2","df" ,"p-value"),row.names=FALSE) %>%
add_header_above(c("coxme(Surv(Time To Death,Censor) ~ Treatment + (1|Repeat))" = 5)) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Variable", "logLik", "Chi2", "df", "p-value"), : objet 'tab_test' introuvable## plot
survdata <- survfit(Surv(TimeToDeath,Censor)~Treatment, data=tab_survival)Error in is.data.frame(data): objet 'tab_survival' introuvabletoplot <- ggplotprep2(survdata, times=c(seq(0,75,by=3)))Error in data.frame(condition = rep(names(x$strata), x$strata), time = x$time, : objet 'survdata' introuvableLimits=c("HS","HY")
Name="Diet"
n1 = survdata$n[1]Error in eval(expr, envir, enclos): objet 'survdata' introuvablen2 = survdata$n[2]Error in eval(expr, envir, enclos): objet 'survdata' introuvableLabels = c(paste("HS (n=",n1,")",sep=""),
paste("HY (n=",n2,")",sep=""))Error in eval(quote(list(...)), env): objet 'n1' introuvablePlot_Fig5S1A=
ggplot(toplot, aes(x=Time,y=Survival))+
geom_line(aes(linetype=Condition,colour=Condition),size=0.6)+
geom_point(aes(shape=Condition,fill=Condition,colour=Condition),size = 2) +
geom_text(data = subset(tab_test, Variable=="(-) Diet"), mapping = aes(x = 10, y = 0.5, label = paste("p=",format(Pvalue,digits=2))),size=3)+
geom_errorbar(data=subset(toplot,Time==27),aes(ymin=lower, ymax=upper,colour=Condition), width=.1, alpha=01, size=1, show.legend=FALSE)+
scale_colour_manual(Name,
limits=Limits,
values=c("#ff9595", "#abefff"),
labels=Labels)+
scale_linetype_manual(Name,
limits=Limits,
values=c("solid","solid"),
labels=Labels)+
scale_fill_manual(Name,
limits=Limits,
values=c(c("#ff9595", "#abefff")),
labels=Labels)+
scale_shape_manual(Name,
limits=Limits,
values=c(24,25),
labels=Labels)+
scale_x_continuous("Days post-eclosion",
limits=c(0, 75),
breaks=c(seq(0,75,by=10)))+
scale_y_continuous("Proportion of survivors",
limits=c(0, 1),breaks=c(0,0.2,0.4,0.6,0.8,1))+
theme(aspect.ratio = 1,
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = c(0.25,0.2),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont-2),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size =Smallfont, colour = "black",face="italic"),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(toplot, aes(x = Time, y = Survival)): objet 'toplot' introuvablePlot_Fig5S1AError in eval(expr, envir, enclos): objet 'Plot_Fig5S1A' introuvable##Export Figure 5S1
p-eIF2α stain is elevated in all cells of the epithelium on HS (A, A’, first row) diet compared to HY (B,B’, second row) diet, and less strongly in visceral muscle (C-D’, third row HS, fourth row HY). In red anti p-eIF2α stain together with EsgTS>UAS-GFP in green (progenitor cells marker) in A, B, or alone in A’, B’. A to B’ are maximum intensity projection of z-stack. In red anti p-eIF2α stain together with HowTS>UAS-GFP in green (Visceral muscle marker) in C, D, or alone in C’, D’ (Single z-stack). Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2A.jpg") Error in transpose(y): object is NULLgob_imageFig5S2A = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2A)Error in grid.draw(gob_imageFig5S2A): objet 'gob_imageFig5S2A' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2A'.jpg") Error in transpose(y): object is NULLgob_imageFig5S2A1 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2A1)Error in grid.draw(gob_imageFig5S2A1): objet 'gob_imageFig5S2A1' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2B.jpg") Error in transpose(y): object is NULLgob_imageFig5S2B = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2B)Error in grid.draw(gob_imageFig5S2B): objet 'gob_imageFig5S2B' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2B'.jpg") Error in transpose(y): object is NULLgob_imageFig5S2B1 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2B1)Error in grid.draw(gob_imageFig5S2B1): objet 'gob_imageFig5S2B1' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2C.jpg") Error in transpose(y): object is NULLgob_imageFig5S2C = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2C)Error in grid.draw(gob_imageFig5S2C): objet 'gob_imageFig5S2C' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2C'.jpg") Error in transpose(y): object is NULLgob_imageFig5S2C1 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2C1)Error in grid.draw(gob_imageFig5S2C1): objet 'gob_imageFig5S2C1' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2D.jpg") Error in transpose(y): object is NULLgob_imageFig5S2D = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2D)Error in grid.draw(gob_imageFig5S2D): objet 'gob_imageFig5S2D' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/5 - S2D'.jpg") Error in transpose(y): object is NULLgob_imageFig5S2D1 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig5S2D1)Error in grid.draw(gob_imageFig5S2D1): objet 'gob_imageFig5S2D1' introuvableBlocking translational inhibition with ActTS>Gcn2-IR or ActTS>LK6-IR is sufficient to increase pH3+ cells in midguts of flies shifted from HY to HS diet. However, ActTS>PEK-IR and ActTS>AMPKα-IR had no effect on the number of pH3+ cells. Statistical comparisons are vs control.
tab_PH3_Translation =
d[["5 - S2E"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_PH3_Translation%>%
group_by(Male.Line)%>%
summarise(Sample_size=n())Error in group_by(., Male.Line): objet 'tab_PH3_Translation' introuvable###Stats
#Gcn2-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","Gcn2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("Control vs Gcn2-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_GCN=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#PEK-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","PEK-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("Control vs PEK-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_PEK=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Lk6-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","Lk6-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("Control vs Lk6-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tmp' introuvabletab_stat_Lk6=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Ampk-IR
tmp = subset(tab_PH3_Translation,!is.na(PH3_positive_cell) & Male.Line%in%c("Control","Ampk-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation' introuvabletmp$Male.Line = factor(tmp$Male.Line,levels = c("Control","Ampk-IR"))Error in factor(tmp$Male.Line, levels = c("Control", "Ampk-IR")): objet 'tmp' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male.Line = as.character(paste("Control vs Ampk-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Ampk=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_PEK,tab_stat_Ampk,tab_stat_Lk6,tab_stat_GCN)Error in eval(quote(list(...)), env): objet 'tab_stat_PEK' introuvableletter_position = aggregate(data=tab_PH3_Translation,PH3_positive_cell ~ Male.Line, max)Error in eval(m$data, parent.frame()): objet 'tab_PH3_Translation' introuvabletab_stat=left_join(tab_stat,letter_position)Error in left_join(tab_stat, letter_position): objet 'tab_stat' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =T))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","letter position","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Genotype + (1 | Repeat)" = 10))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat5S2E = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_PH3_Translation$Female.Line = factor(tab_PH3_Translation$Female.Line, labels = c(expression(italic(paste("Ac",t^{TS},">",sep="")))))Error in factor(tab_PH3_Translation$Female.Line, labels = c(expression(italic(paste("Ac", : objet 'tab_PH3_Translation' introuvablez=max(tab_PH3_Translation$PH3_positive_cell, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_PH3_Translation' introuvablePlot_Fig5S2E=
ggplot(tab_PH3_Translation, aes(x = Male.Line, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
geom_text(data = Sample_size, mapping = aes(x = Male.Line, y = -3, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Female.Line, labeller = label_parsed)+
scale_fill_manual(values="#FFE5E5")+
scale_x_discrete("",
limits=c("Control", "Ampk-IR", "PEK-IR", "Gcn2-IR","Lk6-IR"),
labels=c(expression(italic("Control"), italic(paste("AMPK", alpha, "-IR")), italic("PEK-IR"), italic("Gcn2-IR"), italic("Lk6-IR"))))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-3,64),
breaks=seq(0,62,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black", face = "italic"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_PH3_Translation, aes(x = Male.Line, y = PH3_positive_cell)): objet 'tab_PH3_Translation' introuvablePlot_Fig5S2EError in eval(expr, envir, enclos): objet 'Plot_Fig5S2E' introuvableDespite increased mitotic activity following repression of translational inhibition in ActTS>Gcn2-IR or ActTS>LK6-IR, midgut size was still shrinking on flies shifted from HY to HS diet for 7 days. The statistical comparison is comparing interaction between diet and fly lines. Complete statistical annotation on image can be found in the manuscript’s figure.
tab_length_Translation =
d[["5 - S2F"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,c("Control","Gcn2-IR","Lk6-IR")))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_length_Translation%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_length_Translation' introuvable###Stats
#Gcn2-IR
tmp = subset(tab_length_Translation, Male_Line%in%c("Control","Gcn2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_length_Translation' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet * Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male_Line = as.character(paste("Control interaction vs Gcn2-IR interaction")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Gcn2=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Lk6-IR
tmp = subset(tab_length_Translation, Male_Line%in%c("Control","Lk6-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_length_Translation' introuvablemod.gen = fitme(log(Total_Length_mm) ~ Diet * Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Male_Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Male_Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Male_Line = as.character(paste("Control interaction vs Lk6-IR interaction")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat_Lk6=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_Lk6,tab_stat_Gcn2)Error in eval(quote(list(...)), env): objet 'tab_stat_Lk6' introuvabletab_stat$padj = as.numeric(format(p.adjust(tab_stat$Pvalue, method = "BH"),digits=2,scientific =F))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'format' : objet 'tab_stat' introuvabletab_stat$sig = ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*",
ifelse(tab_stat$padj < 0.01 & tab_stat$padj > 0.001, "**",
ifelse(tab_stat$padj < 0.001, "***", "")))Error in ifelse(tab_stat$padj < 0.05 & tab_stat$padj > 0.01, "*", ifelse(tab_stat$padj < : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Copparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Copparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat5S2F = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_length_Translation$Female_Line = factor(tab_length_Translation$Female_Line, labels = c(expression(italic(paste("Ac",t^{TS},">",sep="")))))Error in factor(tab_length_Translation$Female_Line, labels = c(expression(italic(paste("Ac", : objet 'tab_length_Translation' introuvablePlot_Fig5S2F=
ggplot(tab_length_Translation, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.15) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~ Male_Line)+
scale_fill_manual(values=c("#C3E6FC", "#FFE5E5"))+
scale_x_discrete("",
limits=c("HY D0","HYtoHS D7"),
labels=c("HY","HY to HS"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,9),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0),face = "italic"),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0), face = "italic"),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_Translation, aes(x = Diet, y = Total_Length_mm)): objet 'tab_length_Translation' introuvablePlot_Fig5S2FError in eval(expr, envir, enclos): objet 'Plot_Fig5S2F' introuvableKnockdown of Gcn2 in ECs (MyoTS>Gcn2-IR), but not in progenitor cells (EsgTS>Gcn2-IR), is sufficient to increase pH3+ cells in midguts of flies shifted after 12 days from eclosion on HY to HS diet for additional 7 days. Statistical comparisons are vs respective controls.
tab_PH3_Translation1 =
d[["5 - S2G"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_PH3_Translation1%>%
group_by(Female.Line, Male.Line)%>%
summarise(Sample_size=n())Error in group_by(., Female.Line, Male.Line): objet 'tab_PH3_Translation1' introuvable###Stats
#Esg
tmp = subset(tab_PH3_Translation1,!is.na(PH3_positive_cell) & Female.Line%in%c("Esg"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation1' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Control vs Gcn2-IR EsgTS")),
Male.Line = as.character(paste("EsgTS x Gcn2-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)),
Female.Line = "Esg",
Male.line ="Gcn2-IR")Error in levels(x): objet 'tmp' introuvabletab_stat_esg=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Myo
tmp = subset(tab_PH3_Translation1,!is.na(PH3_positive_cell) & Female.Line%in%c("Myo"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_Translation1' introuvablemod.gen = fitme(log(PH3_positive_cell+1) ~ Male.Line + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(PH3_positive_cell+1) ~ Male.Line + (1 / Repeat),data = tmp)Error in is.data.frame(data): objet 'tmp' introuvablemod.gen1 = fitme(log(PH3_positive_cell+1) ~ 1 + (1 | Repeat),data = tmp)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tmp' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Control vs Gcn2-IR EsgTS")),
Male.Line = as.character(paste("MyoTS x Gcn2-IR")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)),
Female.Line = "Myo",
Male.line ="Gcn2-IR")Error in levels(x): objet 'tmp' introuvabletab_stat_myo=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable#Table making
tab_stat=rbind(tab_stat_esg,tab_stat_myo)Error in eval(quote(list(...)), env): objet 'tab_stat_esg' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Female.Line","Male.Line","Signif."),row.names = FALSE) %>%
add_header_above(c("log(PH3_positive_cell+1) ~ Genotype + (1 | Repeat)" = 11))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Variable", "Replicates", : objet 'tab_stat' introuvabletab_stat5S2G = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_PH3_Translation1$Female.Line = factor(tab_PH3_Translation1$Female.Line, labels = c(expression(italic(paste("Es",g^{TS},">",sep=""))), expression(italic(paste("My",o^{TS},">",sep="")))))Error in factor(tab_PH3_Translation1$Female.Line, labels = c(expression(italic(paste("Es", : objet 'tab_PH3_Translation1' introuvabletab_stat$Female.Line = tab_stat$Female.Line = factor(tab_stat$Female.Line, labels = c(expression(italic(paste("Es",g^{TS},">",sep=""))), expression(italic(paste("My",o^{TS},">",sep="")))))Error in factor(tab_stat$Female.Line, labels = c(expression(italic(paste("Es", : objet 'tab_stat' introuvableSample_size$Female.Line = Sample_size$Female.Line = factor(Sample_size$Female.Line, labels = c(expression(italic(paste("Es",g^{TS},">",sep=""))), expression(italic(paste("My",o^{TS},">",sep="")))))Error in factor(Sample_size$Female.Line, labels = c(expression(italic(paste("Es", : objet 'Sample_size' introuvablez=max(tab_PH3_Translation1$PH3_positive_cell, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_PH3_Translation1' introuvablePlot_Fig5S2G=
ggplot(tab_PH3_Translation1, aes(x = Male.Line, y = PH3_positive_cell))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
geom_text(data = Sample_size, mapping = aes(x = Male.Line, y = -4, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Female.Line, labeller = label_parsed)+
scale_fill_manual(values="#FFE5E5")+
scale_x_discrete("",
limits=c("Control","Gcn2-IR"),
labels=c(expression(italic("Control"),italic("Gcn2-IR"))))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-5,90),
breaks=seq(0,80,by=20))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black", face = "italic"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_PH3_Translation1, aes(x = Male.Line, y = PH3_positive_cell)): objet 'tab_PH3_Translation1' introuvablePlot_Fig5S2GError in eval(expr, envir, enclos): objet 'Plot_Fig5S2G' introuvable##Export Figure 5S2
Mitotic index does not correlate with midgut length. Quantification of pH3+ cells across a selected panel of high and low responder DGRP lines shows that midgut length does not correlate with cell proliferation.
wolb = d[["DGRP_wolbachia_DFD"]]
colnames(wolb) = c("dgrp.id", "wolbachia")Error in `colnames<-`(`*tmp*`, value = c("dgrp.id", "wolbachia")): tentative de modification de 'colnames' sur un objet ayant moins de deux dimensionswolb$dgrp.id = gsub("line_", "", wolb$dgrp.id)
tab_corr_length_cell_DGRP = subset(d[["6A - 7A"]]) Error in subset.default(d[["6A - 7A"]]): l'argument "subset" est manquant, avec aucune valeur par défauttab_corr_length_cell_DGRP = merge(tab_corr_length_cell_DGRP, wolb, by.x="DGRP.number", by.y="dgrp.id", all.x=T, all.y=F)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'merge' : objet 'tab_corr_length_cell_DGRP' introuvablecolnames(tab_corr_length_cell_DGRP) = tolower(colnames(tab_corr_length_cell_DGRP))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'tolower' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'colnames' : objet 'tab_corr_length_cell_DGRP' introuvablecolnames(tab_corr_length_cell_DGRP)[3] = "repl"Error in colnames(tab_corr_length_cell_DGRP)[3] = "repl": objet 'tab_corr_length_cell_DGRP' introuvabletab_corr_length_cell_DGRP$dgrp.number <- as.factor(tab_corr_length_cell_DGRP$dgrp.number)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_corr_length_cell_DGRP' introuvabletab_corr_length_cell_DGRP=
tab_corr_length_cell_DGRP%>%
dplyr::rename(ral=dgrp.number,
len=total.l,
ph3=total.ph3,
ec.area=area)%>%
mutate(ral=paste("Ral",ral,sep="_"))%>%
mutate_if(is.character,as.factor)Error in dplyr::rename(., ral = dgrp.number, len = total.l, ph3 = total.ph3, : objet 'tab_corr_length_cell_DGRP' introuvablegut_mean=
tab_corr_length_cell_DGRP %>%
group_by(ral, diet,cross,gutnumber)%>%
summarize(mean_gut_len=mean(len,na.rm=T),
mean_cell_size=mean(ec.area,na.rm=T),
se_cell_size=sd(ec.area)/ sqrt(length(ec.area[!is.na(ec.area)])),
mean_PH3=mean(ph3,na.rm=T)) %>%
mutate(Group=paste(cross,gutnumber,sep="_"))Error in group_by(., ral, diet, cross, gutnumber): objet 'tab_corr_length_cell_DGRP' introuvablelevels(gut_mean$ral) <- c("Ral 356", "Ral 362", "Ral 370", "Ral 502", "Ral 765", "Ral 853", "Ral 911")Error in levels(gut_mean$ral) <- c("Ral 356", "Ral 362", "Ral 370", "Ral 502", : objet 'gut_mean' introuvablegut_mean$ral <- factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))Error in factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", : objet 'gut_mean' introuvable# stat over all
mod.gen = fitme(log10(I(mean_gut_len/1000)) ~ mean_PH3 + (1 | ral),data = gut_mean)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'gut_mean' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log10(I(mean_gut_len/1000)) ~ mean_PH3 + (1 / ral),data = gut_mean)Error in is.data.frame(data): objet 'gut_mean' introuvablemod.gen1 = fitme(log10(I(mean_gut_len/1000)) ~ 1 + (1 | ral),data =gut_mean)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'gut_mean' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("PH3 cell")),
Number_genotypes = nlevels(gut_mean$ral),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'gut_mean' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log10(I(mean_gut_len/1000)) ~ mean_PH3 + (1 | Genotype)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Variable", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable#stat per line
Cor_PH3=NULL
for(i in unique(gut_mean$ral)){
#print(i)
cor_PH3_HS=
with(subset(gut_mean,ral==i& diet=="HS"),
cor.test(log(mean_gut_len,10),mean_PH3))
cor_PH3_HY=
with(subset(gut_mean,ral==i& diet=="HY"),
cor.test(log(mean_gut_len,10),mean_PH3))
Cor_PH3_tmp = data.frame(ral = as.character(i),
diet=c("HS","HY"),
Cor = c(format(as.numeric(cor_PH3_HS$estimate), digits = 2),format(as.numeric(cor_PH3_HY$estimate), digits = 2)),
Pvalue = c(format(as.numeric(cor_PH3_HS$p.value), digits = 2),format(as.numeric(cor_PH3_HY$p.value), digits = 2)))
Cor_PH3= rbind(Cor_PH3,Cor_PH3_tmp)
}Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'unique' : objet 'gut_mean' introuvableCor_PH3$padj=p.adjust(Cor_PH3$Pvalue,method = "BH")
Cor_PH3$sig= ifelse(Cor_PH3$padj < 0.05 & Cor_PH3$padj > 0.01, "*",
ifelse(Cor_PH3$padj < 0.01 & Cor_PH3$padj > 0.001, "**",
ifelse(Cor_PH3$padj < 0.001, "***", "ns")))
tmp=subset(gut_mean,diet=="HS")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'gut_mean' introuvablestat_position_HS = aggregate(data=tmp,mean_gut_len/1000 ~ ral, max)Error in eval(m$data, parent.frame()): objet 'tmp' introuvablestat_position_HS$diet="HS"Error in stat_position_HS$diet = "HS": objet 'stat_position_HS' introuvabletmp=subset(gut_mean,diet=="HY")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'gut_mean' introuvablestat_position_HY = aggregate(data=tmp,mean_gut_len/1000 ~ ral, max)Error in eval(m$data, parent.frame()): objet 'tmp' introuvablestat_position_HY$diet="HY"Error in stat_position_HY$diet = "HY": objet 'stat_position_HY' introuvablestat_position=rbind(stat_position_HS,stat_position_HY)Error in eval(quote(list(...)), env): objet 'stat_position_HS' introuvablecolnames(stat_position)[2]="Stat_position"Error in colnames(stat_position)[2] = "Stat_position": objet 'stat_position' introuvableCor_PH3 = left_join(Cor_PH3,stat_position)Error in UseMethod("left_join"): pas de méthode pour 'left_join' applicable pour un objet de classe "list"gut_mean$ral <- factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))Error in factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", : objet 'gut_mean' introuvableCor_PH3$ral <- factor(Cor_PH3$ral, levels = c("Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))
Sample_size=
gut_mean%>%
group_by(diet, ral)%>%
summarise(Sample_size=n())%>%
as.data.frame()%>%
mutate(ral=fct_relevel(ral,"Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'gut_mean' introuvablecor_gut_PH3=
ggplot(gut_mean,aes(x=mean_PH3, y=mean_gut_len/1000,group=ral))+
geom_point(aes(color=diet,fill=diet),shape=21,size=0.9)+
geom_text(data = Sample_size, mapping = aes(x = 35, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = Cor_PH3, mapping = aes( x=60,y=7,label = sig),size=3)+
facet_grid(ral~diet)+
scale_y_continuous("Midgut length (mm)")+
scale_x_continuous(expression(paste("pH3" ^ "+", " cells")))+
scale_color_manual("",
limits=c("HS","HY"),
values=palette_diet_2)+
scale_fill_manual("",
limits=c("HS","HY"),
values=palette_diet_2)+
geom_smooth(method="lm",color="black",size=0.5)+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
axis.title.x = element_text(size=Mediumfont,colour="black"),
axis.title.y = element_text(size=Mediumfont),
axis.line.x = element_line(colour="black"),
axis.line.y = element_line(colour="black"),
axis.ticks.x = element_line(),
axis.ticks.y = element_line(),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
panel.grid = element_blank(),
plot.margin = unit(c(0,0,0,0), "cm"),
legend.direction = "vertical",
legend.box = "vertical",
legend.position = "none",
legend.key.height = unit(0.3, "cm"),
legend.key.width= unit(0.3, "cm"),
strip.text.x = element_text(size =Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size =Smallfont, colour = "black",face="italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(color="black",fill=NA),
strip.placement="outside",
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA),
panel.background = element_rect(fill="transparent"))+
guides(shape=guide_legend(ncol=1),
fill=guide_legend(ncol=1),
col=guide_legend(ncol=1))Error in ggplot(gut_mean, aes(x = mean_PH3, y = mean_gut_len/1000, group = ral)): objet 'gut_mean' introuvablecor_gut_PH3Error in eval(expr, envir, enclos): objet 'cor_gut_PH3' introuvableBlocking EGF signaling with UAS-Egfr-IR in progenitor cells (B, right) results in progenitor cells being almost wiped out compared to control (C, left).Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6B.jpg") Error in transpose(y): object is NULLgob_imageFig6B = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6B)Error in grid.draw(gob_imageFig6B): objet 'gob_imageFig6B' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6C.jpg") Error in transpose(y): object is NULLgob_imageFig6C = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6C)Error in grid.draw(gob_imageFig6C): objet 'gob_imageFig6C' introuvablepH3+ counts for EsgTS>Control vs EsgTS> EGFR-IR
tab_PH3_esg =
d[["6D"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_PH3_esg%>%
group_by(Male.Line)%>%
summarise(Sample_size=n())Error in group_by(., Male.Line): objet 'tab_PH3_esg' introuvable###Stats
mod.gen = fitme(PH3_positive_cell ~ Male.Line + (1 | Repeat),data = subset(tab_PH3_esg,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_esg' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(PH3_positive_cell ~ Male.Line + (1 / Repeat),data = subset(tab_PH3_esg,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_esg' introuvablemod.gen1 = fitme(PH3_positive_cell ~ 1 + (1 | Repeat),data = subset(tab_PH3_esg,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_esg' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Control vs Egfr-IR")),
Rep = nlevels(tab_PH3_esg$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_PH3_esg' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("PH3_positive_cell ~ Genotype + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
tab_PH3_esg$Female.Line = factor(tab_PH3_esg$Female.Line, labels = c(expression(italic(paste("Es",g^{TS},">",sep="")))))Error in factor(tab_PH3_esg$Female.Line, labels = c(expression(italic(paste("Es", : objet 'tab_PH3_esg' introuvablePlot_Fig6D=
ggplot(tab_PH3_esg, aes(x = Male.Line, y = PH3_positive_cell))+
geom_boxplot(aes(fill = Diet), colour = "black", size = 0.2,outlier.shape = NA) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.2) +
geom_text(data = Sample_size, mapping = aes(x = Male.Line, y = -0.8, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat,aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 8.5), textsize = 3, vjust = -0.2, manual = TRUE, tip_length = c(0.01, 0.01))+
facet_grid(.~Female.Line, labeller = label_parsed)+
scale_fill_manual(values="#E5E5FF")+
scale_x_discrete("",
limits=c("Cs","Egfr-IR"),
labels=c("Control","Egfr-IR"))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-1,9),
breaks=seq(0,8,by=2))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1, face = "italic"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_PH3_esg, aes(x = Male.Line, y = PH3_positive_cell)): objet 'tab_PH3_esg' introuvablePlot_Fig6DError in eval(expr, envir, enclos): objet 'Plot_Fig6D' introuvableEsgTS>UAS-Egfr-IR midguts are still able to reach a similar length to controls.
tab_length_esg =
d[["6E"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_length_esg%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_length_esg' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet * Male_Line + (1 | Repeat),data = tab_length_esg)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_esg' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Male_Line + (1 / Repeat),data = tab_length_esg)Error in is.data.frame(data): objet 'tab_length_esg' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Male_Line + (1 | Repeat),data = tab_length_esg)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_esg' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Control vs Egfr-IR")),
Rep = nlevels(tab_length_esg$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_length_esg' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_6E=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_6E$Male_Line="Egfr-IR"Error in tab_stat_6E$Male_Line = "Egfr-IR": objet 'tab_stat_6E' introuvable### Plot
tab_length_esg$Female_Line = factor(tab_length_esg$Female_Line, labels = c(expression(italic(paste("Es",g^{TS},">",sep="")))))Error in factor(tab_length_esg$Female_Line, labels = c(expression(italic(paste("Es", : objet 'tab_length_esg' introuvablePlot_Fig6E=
ggplot(tab_length_esg, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.15) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.4, label = paste("(",Sample_size,")",sep="")),size=3)+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18,aes(group=Repeat, colour = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
facet_grid(.~ Male_Line)+
scale_fill_manual(values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=c("HS D0","HStoHY D7"),
labels=c("HS","HS to HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,9),
breaks=seq(2,8,by=1))+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_esg, aes(x = Diet, y = Total_Length_mm)): objet 'tab_length_esg' introuvablePlot_Fig6EError in eval(expr, envir, enclos): objet 'Plot_Fig6E' introuvableInsulin signaling with a dominant negative construct in progenitor cells results in less proliferation
tab_PH3_InR =
d[["6F"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
dplyr::rename(PH3_positive_cell=Total.PH3,
Day_of_treatment=Day)%>%
as.data.frame()%>%
mutate(Male.Line=fct_relevel(Male.Line,c("wdah","InR-DN")))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_PH3_InR%>%
group_by(Male.Line)%>%
summarise(Sample_size=n())Error in group_by(., Male.Line): objet 'tab_PH3_InR' introuvable###Stats
mod.gen = fitme(PH3_positive_cell ~ Male.Line + (1 | Repeat),data = subset(tab_PH3_InR,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_InR' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(PH3_positive_cell ~ Male.Line + (1 / Repeat),data = subset(tab_PH3_InR,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_InR' introuvablemod.gen1 = fitme(PH3_positive_cell ~ 1 + (1 | Repeat),data = subset(tab_PH3_InR,!is.na(PH3_positive_cell)))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_PH3_InR' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Control vs InR-DN")),
Rep = nlevels(tab_PH3_InR$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_PH3_InR' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("PH3_positive_cell ~ Genotype + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
tab_PH3_InR$Female.Line = factor(tab_PH3_InR$Female.Line, labels = c(expression(italic(paste("Es",g^{TS},">",sep="")))))Error in factor(tab_PH3_InR$Female.Line, labels = c(expression(italic(paste("Es", : objet 'tab_PH3_InR' introuvablePlot_Fig6F=
ggplot(tab_PH3_InR, aes(x = Male.Line, y = PH3_positive_cell))+
geom_boxplot(aes(fill = Diet), colour = "black", size = 0.2,outlier.shape = NA) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.6) +
geom_text(data = Sample_size, mapping = aes(x = Male.Line, y = -1.2, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat,aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 16), textsize = 3, vjust = -0.2, manual = TRUE, tip_length = c(0.01, 0.01))+
facet_grid(.~Female.Line, labeller = label_parsed)+
scale_fill_manual(values="#E5E5FF")+
scale_x_discrete("",
limits=c("wdah","InR-DN"),
labels=c("Control","InR-DN"))+
scale_y_continuous(expression(paste("pH3" ^ "+", " cells")),
limits=c(-1.4,21),
breaks=seq(0,20,by=4))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black", margin = margin(t = 0, r = -0.15, b = 0, l = 0, unit = "cm")),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1, face= "italic"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_PH3_InR, aes(x = Male.Line, y = PH3_positive_cell)): objet 'tab_PH3_InR' introuvablePlot_Fig6FError in eval(expr, envir, enclos): objet 'Plot_Fig6F' introuvableEsgTS>UAS-InR-DN resulting in the same midgut length growth as the control. Statistical comparison for G is for the interaction between diet and genotype.
tab_length_InDN =
subset(d[["6G"]],Diet%in%c("HS D0","HStoHY D7"))%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,c("Control","InR-DN")))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction '%in%' : objet 'Diet' introuvableSample_size=
tab_length_InDN%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_length_InDN' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet * Male_Line + (1 | PhaseRep),data = tab_length_InDN)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_InDN' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Male_Line + (1 / PhaseRep),data = tab_length_InDN)Error in is.data.frame(data): objet 'tab_length_InDN' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Male_Line + (1 | PhaseRep),data = tab_length_InDN)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_InDN' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Control vs InR-DN")),
Rep = nlevels(tab_PH3_esg$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_PH3_esg' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_length_mm) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat$Male_Line="InR-DN"Error in tab_stat$Male_Line = "InR-DN": objet 'tab_stat' introuvabletab_stat6G = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_length_InDN$Male_Line = factor(tab_length_InDN$Male_Line, labels = c("Control","InR-DN"))Error in factor(tab_length_InDN$Male_Line, labels = c("Control", "InR-DN")): objet 'tab_length_InDN' introuvableSample_size$Male_Line = factor(Sample_size$Male_Line, labels = c("Control","InR-DN"))Error in factor(Sample_size$Male_Line, labels = c("Control", "InR-DN")): objet 'Sample_size' introuvablePlot_Fig6G=
ggplot(tab_length_InDN, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.15) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Male_Line)+
scale_fill_manual(values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=c("HS D0","HStoHY D7"),
labels=c("HS","HS to HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,9),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_InDN, aes(x = Diet, y = Total_Length_mm)): objet 'tab_length_InDN' introuvablePlot_Fig6GError in eval(expr, envir, enclos): objet 'Plot_Fig6G' introuvableIncrease in midgut length despite proliferation blockage is accompanied with compensatory area increase of EC. Representative pictures of midguts stained with membrane marker Mesh (white), shifted from HS to HY for 7 days show bigger cells on EsgTS>UAS-Egfr-IR (I, right) compared to control (H, left). Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6H.jpg") Error in transpose(y): object is NULLgob_imageFig6H = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6H)Error in grid.draw(gob_imageFig6H): objet 'gob_imageFig6H' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6I.jpg") Error in transpose(y): object is NULLgob_imageFig6I = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6I)Error in grid.draw(gob_imageFig6I): objet 'gob_imageFig6I' introuvableQuantification of EC cell size shows compensatory effect in ECs of EsgTS>Egfr-IR.Statistical comparison is for the interaction between diet and genotype.
tab_area_esg =
subset(d[["6J"]],Area<=1300)%>%
mutate_at(vars(!starts_with("Area")),as.factor)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Diet=fct_relevel(Diet,c("HS", "HStoHY")))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'Area' introuvableSample_size=
tab_area_esg%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_area_esg' introuvable###Stats
# D7
mod.gen = fitme(log(Area) ~ Diet * Male_Line + (1 | Repeat) ,data = tab_area_esg)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_area_esg' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Area) ~ Diet * Male_Line+ (1 / Repeat) ,data = tab_area_esg)Error in is.data.frame(data): objet 'tab_area_esg' introuvablemod.gen1 = fitme(log(Area) ~ Diet + Male_Line + (1 | Repeat),data = tab_area_esg)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_area_esg' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Response Control vs Egfr")),
Rep = nlevels(tab_area_esg$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[4],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_area_esg' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Cell area) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Variable", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_6J=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_6J$Male_Line="Egfr-IR"Error in tab_stat_6J$Male_Line = "Egfr-IR": objet 'tab_stat_6J' introuvabletab_stat_6J$Diet=c("HStoHY")Error in tab_stat_6J$Diet = c("HStoHY"): objet 'tab_stat_6J' introuvabletab_stat_6J$yposition = c(0.6)Error in tab_stat_6J$yposition = c(0.6): objet 'tab_stat_6J' introuvabletab_stat_6J$xposition = c(1.5)Error in tab_stat_6J$xposition = c(1.5): objet 'tab_stat_6J' introuvable### Plot
z = max(tab_area_esg$Area/1000, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_area_esg' introuvablePlot_Fig6J=
ggplot(tab_area_esg, aes(x = Diet, y = Area/1000))+
geom_violin(aes(fill = C.G), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 2) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/120) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -0.1, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Male_Line)+
scale_fill_manual(values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=c("HS","HStoHY"),
labels=c("HS","HS to HY"))+
scale_y_continuous(expression(paste("EC area (10"^3, "mm"^2,")",sep="")),
limits=c(-0.1,1.1),
breaks=seq(0,1.1,by=0.4))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(margin(0, 0, 0, 0, unit = "cm")),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text = element_text(size =Smallfont, colour = "black",face="italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_area_esg, aes(x = Diet, y = Area/1000)): objet 'tab_area_esg' introuvablePlot_Fig6JError in eval(expr, envir, enclos): objet 'Plot_Fig6J' introuvable##Export Figure 6
Changes in the number of pH3+ cells between HS and HY (ratio HY/HS of mean pH3+ cells) does not correlate with changes in midgut size between HS and HY (ratio HY/HS of mean midgut length) across selected DGRP lines.
tab_corr_length_cell_DGRP_mean_ph3 =
tab_corr_length_cell_DGRP%>%
group_by(ral,diet)%>%
summarise(mean_ph3=mean(ph3,na.rm=T))%>%
spread(diet,mean_ph3)%>%
dplyr::rename(Mean_ph3_HS=HS,
Mean_ph3_HY=HY)%>%
mutate(Ratio_ph3 = Mean_ph3_HY/Mean_ph3_HS)Error in group_by(., ral, diet): objet 'tab_corr_length_cell_DGRP' introuvabletab_corr_length_cell_DGRP_mean_length =
tab_corr_length_cell_DGRP%>%
group_by(ral,diet)%>%
summarise(mean_length=mean(len,na.rm=T))%>%
spread(diet,mean_length)%>%
dplyr::rename(mean_length_HS=HS,
mean_length_HY=HY)%>%
mutate(Ratio_length = mean_length_HY/mean_length_HS)Error in group_by(., ral, diet): objet 'tab_corr_length_cell_DGRP' introuvabletab_corr_length_cell_DGRP_mean= left_join(tab_corr_length_cell_DGRP_mean_length,tab_corr_length_cell_DGRP_mean_ph3)Error in left_join(tab_corr_length_cell_DGRP_mean_length, tab_corr_length_cell_DGRP_mean_ph3): objet 'tab_corr_length_cell_DGRP_mean_length' introuvabletab_corr_length_cell_DGRP_mean=as.data.frame(tab_corr_length_cell_DGRP_mean)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_corr_length_cell_DGRP_mean' introuvabletest =
with(tab_corr_length_cell_DGRP_mean,
cor.test(Ratio_ph3,Ratio_length,method="pearson"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'data' lors de la s�lection d'une m�thode pour la fonction 'with' : objet 'tab_corr_length_cell_DGRP_mean' introuvabletab_stat = data.frame(Statistic = test$statistic,
cor = test$estimate,
Pvalue = test$p.value)Error in test$statistic: objet de type 'closure' non indiçablelevels(tab_corr_length_cell_DGRP_mean$ral) <- c("Ral 356", "Ral 362", "Ral 370", "Ral 502", "Ral 765", "Ral 853", "Ral 911" )Error in levels(tab_corr_length_cell_DGRP_mean$ral) <- c("Ral 356", "Ral 362", : objet 'tab_corr_length_cell_DGRP_mean' introuvablePlot_Fig6S1A =
ggplot(tab_corr_length_cell_DGRP_mean,aes(x=Ratio_ph3,y=Ratio_length,label=ral))+
geom_point()+
scale_x_continuous(expression(paste("Ratio HY/HS (mean pH3" ^ "+", " cells)")),
limits=c(0.8,1.8),
breaks=c(seq(0.8,2.8,by=0.1)))+
scale_y_continuous("Ratio HY/HS (mean midgut length)",
limits=c(0.8,1.8),
breaks=c(seq(0.8,2.8,by=0.2)))+
geom_text_repel(data=tab_corr_length_cell_DGRP_mean,size=3)+
geom_smooth(method="lm")+
geom_text(data = tab_stat, mapping = aes(x = 1.6, y = 1.7, label = paste("cor=", format(cor, digits=2), "p=",format(Pvalue,digits=2))),size=3)+ theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
(panel.border = element_blank()),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_blank(),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = c(0.25,0.98),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.4, "cm"),
legend.title = element_blank(),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA))+
guides(color=guide_legend(ncol=3))Error in ggplot(tab_corr_length_cell_DGRP_mean, aes(x = Ratio_ph3, y = Ratio_length, : objet 'tab_corr_length_cell_DGRP_mean' introuvablePlot_Fig6S1AError in eval(expr, envir, enclos): objet 'Plot_Fig6S1A' introuvableOverexpression of reaper in progenitor cells (marked in red) via EsgTS>rpr-OE results in loss of marked progenitor cells (C) compared to control (B) in region 4 of midguts, after 12 days post eclosion on HS diet (7 days at 29°C with TARGET system active). Shifting the flies on HY for additional 7 days results in a change in morphology on midguts overexpressing reaper, reminiscent of EsgTS>UAS-Egfr-IR midguts .Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6 - S1B.jpg") Error in transpose(y): object is NULLgob_imageFig6S1B = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6S1B)Error in grid.draw(gob_imageFig6S1B): objet 'gob_imageFig6S1B' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6 - S1C.jpg") Error in transpose(y): object is NULLgob_imageFig6S1C = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6S1C)Error in grid.draw(gob_imageFig6S1C): objet 'gob_imageFig6S1C' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6 - S1D.jpg") Error in transpose(y): object is NULLgob_imageFig6S1D = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6S1D)Error in grid.draw(gob_imageFig6S1D): objet 'gob_imageFig6S1D' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/6 - S1E.jpg") Error in transpose(y): object is NULLgob_imageFig6S1E = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig6S1E)Error in grid.draw(gob_imageFig6S1E): objet 'gob_imageFig6S1E' introuvableEsgTS> rpr-OE midguts are still able to reach a similar length to controls .Complete graphical annotation can be found in manuscript figures
tab_length_rpr =
d[["6 - S1F"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line, "Control", "rpr-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_length_rpr%>%
group_by(Diet, Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_length_rpr' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet * Male_Line + (1 | Repeat),data = tab_length_rpr)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_rpr' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Male_Line + (1 / Repeat),data = tab_length_rpr)Error in is.data.frame(data): objet 'tab_length_rpr' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Male_Line + (1 | Repeat),data = tab_length_rpr)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_rpr' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvabletestfunction (pkg = ".", filter = NULL, stop_on_failure = FALSE,
export_all = TRUE, ...)
{
save_all()
pkg <- as.package(pkg)
if (!uses_testthat(pkg) && interactive()) {
cli::cli_alert_danger("No testing infrastructure found. Create it?")
if (utils::menu(c("Yes", "No")) == 1) {
usethis_use_testthat(pkg)
}
return(invisible())
}
load_all(pkg$path)
cli::cli_alert_info("Testing {.pkg {pkg$package}}")
withr::local_envvar(r_env_vars())
testthat::test_local(pkg$path, filter = filter, stop_on_failure = stop_on_failure,
...)
}
<bytecode: 0x000000009e53be20>
<environment: namespace:devtools>Chi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Interaction Control vs Interaction Rpr-OE")),
Male_Line = as.character(paste("rpr-OE")),
Rep = nlevels(tmp$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tmp' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat_rpr=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_rpr%>%
kable(col.names = c("Comparison", "Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Variable", "Replicates", : objet 'tab_stat_rpr' introuvable### Plot
z = max(tab_length_rpr$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_length_rpr' introuvablePlot_Fig6S1F=
ggplot(tab_length_rpr, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/40) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Male_Line )+
scale_fill_manual(values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=c("HS","HStoHY"),
labels=c("HS","HS to HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,9),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = xSmallfont, colour = "black", angle=0, face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = xSmallfont, colour = "black", angle=0, face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_rpr, aes(x = Diet, y = Total_Length_mm)): objet 'tab_length_rpr' introuvablePlot_Fig6S1FError in eval(expr, envir, enclos): objet 'Plot_Fig6S1F' introuvable##Export Figure 6 - supplementary 1
Enterocyte size mostly correlates with midgut length. Quantification of EC area across a selected panel of DGRP lines comprising high and low responder shows that midgut length mostly correlates with EC cell area. Lines on plot show smoothed splines.
wolb = d[["DGRP_wolbachia_DFD"]]
colnames(wolb) = c("dgrp.id", "wolbachia")Error in `colnames<-`(`*tmp*`, value = c("dgrp.id", "wolbachia")): tentative de modification de 'colnames' sur un objet ayant moins de deux dimensionswolb$dgrp.id = gsub("line_", "", wolb$dgrp.id)
tab_corr_length_cell_DGRP = subset(d[["6A - 7A"]]) Error in subset.default(d[["6A - 7A"]]): l'argument "subset" est manquant, avec aucune valeur par défauttab_corr_length_cell_DGRP = merge(tab_corr_length_cell_DGRP, wolb, by.x="DGRP.number", by.y="dgrp.id", all.x=T, all.y=F)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'merge' : objet 'tab_corr_length_cell_DGRP' introuvablecolnames(tab_corr_length_cell_DGRP) = tolower(colnames(tab_corr_length_cell_DGRP))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'tolower' : erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'colnames' : objet 'tab_corr_length_cell_DGRP' introuvablecolnames(tab_corr_length_cell_DGRP)[3] = "repl"Error in colnames(tab_corr_length_cell_DGRP)[3] = "repl": objet 'tab_corr_length_cell_DGRP' introuvabletab_corr_length_cell_DGRP=
tab_corr_length_cell_DGRP%>%
dplyr::rename(ral=dgrp.number,
len=total.l,
ph3=total.ph3,
ec.area=area)%>%
mutate(ral=paste("Ral",ral,sep="_"))%>%
mutate_if(is.character,as.factor)Error in dplyr::rename(., ral = dgrp.number, len = total.l, ph3 = total.ph3, : objet 'tab_corr_length_cell_DGRP' introuvablegut_mean=
tab_corr_length_cell_DGRP %>%
group_by(ral, diet,cross,gutnumber)%>%
summarize(mean_gut_len=mean(len,na.rm=T),
mean_cell_size=mean(ec.area,na.rm=T),
se_cell_size=sd(ec.area,na.rm=T)/ sqrt(length(ec.area[!is.na(ec.area)])),
mean_PH3=mean(ph3,na.rm=T)) %>%
mutate(Group=paste(cross,gutnumber,sep="_"))Error in group_by(., ral, diet, cross, gutnumber): objet 'tab_corr_length_cell_DGRP' introuvablelevels(gut_mean$ral) <- c("Ral 356", "Ral 362", "Ral 370", "Ral 502", "Ral 765", "Ral 853", "Ral 911" )Error in levels(gut_mean$ral) <- c("Ral 356", "Ral 362", "Ral 370", "Ral 502", : objet 'gut_mean' introuvablegut_mean$ral <- factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))Error in factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", : objet 'gut_mean' introuvableSample_size=
gut_mean%>%
group_by(diet, ral)%>%
summarise(Sample_size=n())%>%
as.data.frame()%>%
mutate(ral=fct_relevel(ral,"Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'gut_mean' introuvable# stat over all
mod.gen = fitme(log10(I(mean_gut_len/1000)) ~ mean_cell_size + (1 | ral),data = gut_mean)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'gut_mean' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log10(I(mean_gut_len/1000)) ~ mean_cell_size + (1 / ral),data = gut_mean)Error in is.data.frame(data): objet 'gut_mean' introuvablemod.gen1 = fitme(log10(I(mean_gut_len/1000)) ~ 1 + (1 | ral),data =gut_mean)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'gut_mean' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Cell area")),
Number_genotypes = nlevels(gut_mean$ral),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'gut_mean' introuvable#stat per line
Cor_area=NULL
for(i in unique(gut_mean$ral)){
# print(i)
Cor_area_HS=
with(subset(gut_mean,ral==i& diet=="HS"),
cor.test(log(mean_gut_len,2),mean_cell_size))
Cor_area_HY=
with(subset(gut_mean,ral==i& diet=="HY"),
cor.test(log(mean_gut_len,2),mean_cell_size))
Cor_area_tmp = data.frame(ral = as.character(i),
diet=c("HS","HY"),
Cor = c(format(as.numeric(Cor_area_HS$estimate), digits = 2),format(as.numeric(Cor_area_HY$estimate), digits = 2)),
Pvalue = c(format(as.numeric(Cor_area_HS$p.value), digits = 2),format(as.numeric(Cor_area_HY$p.value), digits = 2)))
Cor_area= rbind(Cor_area,Cor_area_tmp)
}Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'unique' : objet 'gut_mean' introuvableCor_area$padj=p.adjust(Cor_area$Pvalue,method = "BH")
Cor_area$sig= ifelse(Cor_area$padj < 0.05 & Cor_area$padj > 0.01, "*",
ifelse(Cor_area$padj < 0.01 & Cor_area$padj > 0.001, "**",
ifelse(Cor_area$padj < 0.001, "***", "ns")))
tmp=subset(gut_mean,diet=="HS")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'gut_mean' introuvablestat_position_HS = aggregate(data=tmp,mean_gut_len/1000 ~ ral, max)Error in eval(m$data, parent.frame()): objet 'tmp' introuvablestat_position_HS$diet="HS"Error in stat_position_HS$diet = "HS": objet 'stat_position_HS' introuvabletmp=subset(gut_mean,diet=="HY")Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'gut_mean' introuvablestat_position_HY = aggregate(data=tmp,mean_gut_len/1000 ~ ral, max)Error in eval(m$data, parent.frame()): objet 'tmp' introuvablestat_position_HY$diet="HY"Error in stat_position_HY$diet = "HY": objet 'stat_position_HY' introuvablestat_position=rbind(stat_position_HS,stat_position_HY)Error in eval(quote(list(...)), env): objet 'stat_position_HS' introuvablecolnames(stat_position)[2]="Stat_position"Error in colnames(stat_position)[2] = "Stat_position": objet 'stat_position' introuvableCor_area = left_join(Cor_area,stat_position)Error in UseMethod("left_join"): pas de méthode pour 'left_join' applicable pour un objet de classe "list"gut_mean$ral <- factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))Error in factor(gut_mean$ral, levels = c("Ral 356", "Ral 502", "Ral 765", : objet 'gut_mean' introuvableCor_area$ral <- factor(Cor_area$ral, levels = c("Ral 356", "Ral 502", "Ral 765", "Ral 853", "Ral 911", "Ral 362", "Ral 370"))
Plot_Fig7A=
ggplot(gut_mean,aes(x=log2(mean_cell_size), y=mean_gut_len/1000,group=ral))+
geom_point( aes(color=diet,fill=diet),shape=21,size=0.9)+
geom_text(data = Sample_size, mapping = aes(x = 8, y = 2.5, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = Cor_area, mapping = aes( x=7,y=7,label = sig),size=3)+
facet_grid(ral~diet)+
scale_y_continuous("Midgut length (mm)")+
scale_x_continuous(expression(paste("Cell size (", log[2],"(mean\u00B1se))")))+
scale_color_manual("",
limits=c("HS","HY"),
values=palette_diet_2)+
scale_fill_manual("",
limits=c("HS","HY"),
values=palette_diet_2)+
geom_smooth(method="lm",color="black",size=0.5)+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(gut_mean, aes(x = log2(mean_cell_size), y = mean_gut_len/1000, : objet 'gut_mean' introuvablePlot_Fig7AError in eval(expr, envir, enclos): objet 'Plot_Fig7A' introuvableRepresentative pictures of single cell clones (hsFlp; Act>STOP>Gal4, UAS-GFP) suggest that compared to GFP- cells, TOR downregulation (UAS-Tor-IR, GFP+) results in smaller cells, while TOR hyperactivity (UAS-Rheb-OE, C) increases cell size. Quantification of clone size in D. Single cell clones are marked with GFP (green). Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7B.jpg") Error in transpose(y): object is NULLgob_imageFig7B = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7B)Error in grid.draw(gob_imageFig7B): objet 'gob_imageFig7B' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7C.jpg") Error in transpose(y): object is NULLgob_imageFig7C = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7C)Error in grid.draw(gob_imageFig7C): objet 'gob_imageFig7C' introuvabletab_ECclone_quant =
d[["7D"]]%>%
mutate_at(vars(!starts_with("Area")),as.factor)%>%
dplyr::rename(Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,"Tor-IR","Rheb-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_ECclone_quant%>%
group_by(Male_Line, GFP)%>%
summarise(Sample_size=n())%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,"Tor-IR","Rheb-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_ECclone_quant' introuvable###Stats
#Tor-IR stats
mod.gen = fitme(log(Area) ~ GFP,data = subset(tab_ECclone_quant, Male_Line=="Tor-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Area) ~ GFP ,data = subset(tab_ECclone_quant, Male_Line=="Tor-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant' introuvablemod.gen1 = fitme(log(Area) ~ 1 ,data = subset(tab_ECclone_quant, Male_Line=="Tor-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("GFP Negative vs Positive (Tor-IR)")),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in test$basicLRT: objet de type 'closure' non indiçabletab_stat_TorEC = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvablemod.gen = fitme(log(Area) ~ GFP,data = subset(tab_ECclone_quant, Male_Line=="Rheb-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Area) ~ GFP ,data = subset(tab_ECclone_quant, Male_Line=="Rheb-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant' introuvablemod.gen1 = fitme(log(Area) ~ 1 ,data = subset(tab_ECclone_quant, Male_Line=="Rheb-OE"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("GFP Negative vs Positive (Rheb-OE)")),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in test$basicLRT: objet de type 'closure' non indiçabletab_stat_RhebOEEC = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat=rbind(tab_stat_TorEC,tab_stat_RhebOEEC)Error in eval(quote(list(...)), env): objet 'tab_stat_TorEC' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat$Male_Line = as.factor(c("Tor-IR","Rheb-OE"))Error in tab_stat$Male_Line = as.factor(c("Tor-IR", "Rheb-OE")): objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Chi2", "Intercept","Estimate","df" ,"p-value", "Signif.", "RNAi line"),row.names = FALSE) %>% add_header_above(c("log(Cell area) ~ GFP" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Chi2", "Intercept", "Estimate", : objet 'tab_stat' introuvable### Plot
Plot_Fig7D=
ggplot(tab_ECclone_quant, aes(x = GFP, y = Area/1000))+
geom_violin(aes(fill = GFP), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.04) +
geom_text(data = Sample_size, mapping = aes(x = GFP, y = -0.2, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat,aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 2), textsize = 3, vjust = -0.2, manual = TRUE, tip_length = c(0.01, 0.01))+
facet_grid(.~Male_Line)+
scale_fill_manual(limits=c("No","Yes"),
values=c("#e4e4e4","#8ee53f"))+
scale_x_discrete("GFP",
limits=c("No","Yes"),
labels=c("-","+"))+
scale_y_continuous(expression(paste("EC area (10"^3, "mm"^2,")",sep="")),
limits=c(-0.3,2.3),
breaks=seq(0,2,by=0.4))+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, colour = "yellow") +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black", vjust = 6),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_ECclone_quant, aes(x = GFP, y = Area/1000)): objet 'tab_ECclone_quant' introuvablePlot_Fig7DError in eval(expr, envir, enclos): objet 'Plot_Fig7D' introuvableKnockdown of TOR with MyoTS, an EC-specific driver, leads to the increased number of small ECs (F, right) compared to control (E, left); EC-specific GFP is indeed visible in small cells.Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7E.jpg") Error in transpose(y): object is NULLgob_imageFig7E = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7E)Error in grid.draw(gob_imageFig7E): objet 'gob_imageFig7E' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7F.jpg") Error in transpose(y): object is NULLgob_imageFig7F = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7F)Error in grid.draw(gob_imageFig7F): objet 'gob_imageFig7F' introuvableQuantification of EC area. Statistic annotation on panel present in manuscript’s figure.
tab_area_Tor_IR =
d[["7G"]]%>%
mutate_at(vars(!starts_with("Area")),as.factor)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Diet=fct_relevel(Diet,c("HS", "HStoHY")),
Male_Line=fct_relevel(Male_Line,c("Control","Tor-IR")))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_area_Tor_IR%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_area_Tor_IR' introuvable###Stats Tor
# D7
mod.gen = fitme(log(Area) ~ Diet * Male_Line + (1 | Repeat ) ,data = tab_area_Tor_IR)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_area_Tor_IR' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Area) ~ Diet * Male_Line + (1 / Repeat ) ,data = tab_area_Tor_IR)Error in is.data.frame(data): objet 'tab_area_Tor_IR' introuvablemod.gen1 = fitme(log(Area) ~ Diet + Male_Line + (1 | Repeat ),data = tab_area_Tor_IR)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_area_Tor_IR' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character("Control vs Tor-IR"),
Rep = nlevels(tab_area_Tor_IR$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[4],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_area_Tor_IR' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Response to diet", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Cell area) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Response to diet", "Replicates", "Chi2", : objet 'tab_stat' introuvabletab_stat_7E=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_7E$Male_Line=factor("Tor-IR", labels = c(expression(italic("Tor-IR"))))Error in tab_stat_7E$Male_Line = factor("Tor-IR", labels = c(expression(italic("Tor-IR")))): objet 'tab_stat_7E' introuvabletab_stat_7E$Diet=c("HStoHY")Error in tab_stat_7E$Diet = c("HStoHY"): objet 'tab_stat_7E' introuvabletab_stat_7E$yposition = c(0.7)Error in tab_stat_7E$yposition = c(0.7): objet 'tab_stat_7E' introuvabletab_stat_7E$xposition = c(1.5)Error in tab_stat_7E$xposition = c(1.5): objet 'tab_stat_7E' introuvable### Plot
tab_area_Tor_IR$Female_Line = factor(tab_area_Tor_IR$Female_Line, labels = c(expression(italic(paste("My",o^{TS},">",sep="")))))Error in factor(tab_area_Tor_IR$Female_Line, labels = c(expression(italic(paste("My", : objet 'tab_area_Tor_IR' introuvabletab_area_Tor_IR$Male_Line = factor(tab_area_Tor_IR$Male_Line, labels = c(expression(italic("Control"),italic("Tor-IR"))))Error in factor(tab_area_Tor_IR$Male_Line, labels = c(expression(italic("Control"), : objet 'tab_area_Tor_IR' introuvableSample_size$Male_Line = factor(Sample_size$Male_Line, labels = c(expression(italic("Control"),italic("Tor-IR"))))Error in factor(Sample_size$Male_Line, labels = c(expression(italic("Control"), : objet 'Sample_size' introuvablePlot_Fig7G=
ggplot(tab_area_Tor_IR, aes(x = Diet, y = Area/1000))+
geom_violin(aes(fill = C.G), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 5) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.008) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -0.1, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Male_Line,labeller=label_parsed )+
scale_fill_manual(values=c("#FFB4B4", "#CCCCFF"))+
scale_x_discrete("",
limits=c("HS","HStoHY"),
labels=c("HS","HS to HY"))+
scale_y_continuous(expression(paste("EC area (10"^3, "mm"^2,")",sep="")),
limits=c(-0.12,1),
breaks=seq(0,0.8,by=0.2))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text = element_text(size =Smallfont, colour = "black",face="italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_area_Tor_IR, aes(x = Diet, y = Area/1000)): objet 'tab_area_Tor_IR' introuvablePlot_Fig7GError in eval(expr, envir, enclos): objet 'Plot_Fig7G' introuvableBlocking TOR pathway components in ECs (MyoTS) inhibits diet induced midgut growth. Control showed in chart is representative of multiple experiments. Statistical analyses were performed only on appropriate repeat/experiment and comparing interaction between diet and fly line.
tab_length_Tor =
d[["7H"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line, "Control", "Tor-IR","dMyc-IR","S6k-IR", "SREBP-IR", "raptor-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_length_Tor%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Male_Line): objet 'tab_length_Tor' introuvable###Stats
list_genotype= c("Tor-IR","dMyc-IR","S6k-IR", "SREBP-IR", "raptor-IR")
tab_stat_Tor=NULL
for (i in list_genotype){
list_control=
subset(tab_length_Tor,Male_Line%in%c(i)) %>%
mutate(PhaseRep=factor(PhaseRep))%>%
summarise(levels(PhaseRep))
list_control = as.list(list_control$`levels(PhaseRep)`)
tmp= subset(tab_length_Tor, Male_Line%in%c(i, "Control") & PhaseRep%in%list_control)%>%
mutate(Male_Line=factor(Male_Line),
PhaseRep=factor(PhaseRep))
mod.gen = fitme(log10(Total_Length_mm) ~ Diet * Male_Line + (1 | PhaseRep),data = tmp)
shapiro.test(residuals(mod.gen))
bptest(log10(Total_Length_mm) ~ Diet + Male_Line + (1 / PhaseRep),data = tmp)
mod.gen1 = fitme(log10(Total_Length_mm) ~ Diet + Male_Line + (1 | PhaseRep),data = tmp)
test = anova(mod.gen, mod.gen1)
test
Chi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])
tab_stat = data.frame(Male_Line = as.character(i),
Rep = nlevels(tmp$PhaseRep),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[4],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))
tab_stat_Tor = rbind(tab_stat_Tor,tab_stat)
}Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_length_Tor' introuvabletab_stat_Tor$padj=p.adjust(tab_stat_Tor$Pvalue,method = "BH")
tab_stat_Tor$sig= ifelse(tab_stat_Tor$padj < 0.05 & tab_stat_Tor$padj > 0.01, "*",
ifelse(tab_stat_Tor$padj < 0.01 & tab_stat_Tor$padj > 0.001, "**",
ifelse(tab_stat_Tor$padj < 0.001, "***", "ns")))
tab_stat_Tor%>%
kable(col.names = c("Response to diet", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","p-value adjusted","Signif."),row.names = FALSE) %>% add_header_above(c("log10(Total_Length_mm) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in dimnames(x) <- dn: la longueur de 'dimnames' [2] n'est pas égale à l'étendue du tableautab_stat_Tor=
tab_stat_Tor%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line, "Tor-IR","dMyc-IR","S6k-IR", "SREBP-IR", "raptor-IR"))Error: Problem with `mutate()` column `Male_Line`.
i `Male_Line = fct_relevel(...)`.
x objet 'Male_Line' introuvable### Plot
tab_length_Tor$Female_Line = factor(tab_length_Tor$Female_Line, labels = c(expression(italic(paste("My",o^{TS},">",sep="")))))Error in factor(tab_length_Tor$Female_Line, labels = c(expression(italic(paste("My", : objet 'tab_length_Tor' introuvablez = max(tab_length_Tor$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_length_Tor' introuvablePlot_Fig7H=
ggplot(tab_length_Tor, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/80) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.4, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_stat_Tor, mapping = aes(x = 1.5, y = 8.3, label = paste("p=",format(Pvalue,digits=2))),size=3)+
facet_grid(.~Male_Line )+
scale_fill_manual(values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=c("HS","HStoHY"),
labels=c("HS","HS to HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8.3),
breaks=seq(2,8,by=1))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = PhaseRep)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = PhaseRep, colour = PhaseRep)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = PhaseRep)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = xSmallfont, colour = "black", angle=0, face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = xSmallfont, colour = "black", angle=0, face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_Tor, aes(x = Diet, y = Total_Length_mm)): objet 'tab_length_Tor' introuvablePlot_Fig7HError in eval(expr, envir, enclos): objet 'Plot_Fig7H' introuvable:::
Representative picture utilizing single cell clonal system suggests that blocking Atg2 (hsFlp; Act>STOP>Gal4, UAS-GFP >UAS-Atg2-IR, GFP+ cells) results in bigger ECs compared to control GFP- cells, quantified in J Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7I.jpg") Error in transpose(y): object is NULLgob_imageFig7I = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7I)Error in grid.draw(gob_imageFig7I): objet 'gob_imageFig7I' introuvable:::
tab_ECclone_quant1 =
d[["7J"]]%>%
mutate_at(vars(!starts_with("Area")),as.factor)%>%
dplyr::rename(Male_Line=Male.Line)%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_ECclone_quant1%>%
group_by(GFP)%>%
summarise(Sample_size=n())%>%
as.data.frame()Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_ECclone_quant1' introuvable###Stats
mod.gen = fitme(log(Area) ~ GFP,data = subset(tab_ECclone_quant1, Male_Line=="Atg2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant1' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Area) ~ GFP ,data = subset(tab_ECclone_quant1, Male_Line=="Atg2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant1' introuvablemod.gen1 = fitme(log(Area) ~ 1 ,data = subset(tab_ECclone_quant1, Male_Line=="Atg2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'subset' : objet 'tab_ECclone_quant1' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("GFP Negative vs Positive (Atg2-IR)")),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in test$basicLRT: objet de type 'closure' non indiçabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat$Male_Line = as.factor(c("Atg2-IR"))Error in tab_stat$Male_Line = as.factor(c("Atg2-IR")): objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Chi2", "Intercept","Estimate","df" ,"p-value","Signif.", "RNAi line"),row.names = FALSE) %>% add_header_above(c("log(Cell area) ~ GFP" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Chi2", "Intercept", "Estimate", : objet 'tab_stat' introuvable### Plot
Plot_Fig7J=
ggplot(tab_ECclone_quant1, aes(x = GFP, y = Area/1000))+
geom_violin(aes(fill = GFP), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.03) +
geom_text(data = Sample_size, mapping = aes(x = GFP, y = -0.08, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(data = tab_stat,aes(xmin = 1, xmax = 2, annotations = formatC(paste("p=",Pvalue), digits = 2), y_position = 0.9), textsize = 3, vjust = -0.2, manual = TRUE, tip_length = c(0.01, 0.01))+
facet_grid(.~Male_Line)+
scale_fill_manual(limits=c("No","Yes"),
values=c("#e4e4e4","#8ee53f"))+
scale_x_discrete("GFP",
limits=c("No","Yes"),
labels=c("-","+"))+
scale_y_continuous(expression(paste("EC area (10"^3, "mm"^2,")",sep="")),
limits=c(-0.1,1),
breaks=seq(0,2,by=0.4))+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, colour = "yellow") +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_ECclone_quant1, aes(x = GFP, y = Area/1000)): objet 'tab_ECclone_quant1' introuvablePlot_Fig7JError in eval(expr, envir, enclos): objet 'Plot_Fig7J' introuvableBlocking autophagy reduces midgut resizing upon shrinkage (HY to HS for 7 days). Blocking Atg8a expression with RNAi in ECs (MyoTS> UAS-Atg8a-IR) results in less length shrinkage compared to control midguts.
tab_length_Atg8a =
d[["7K"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,"Control","Atg8a-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_length_Atg8a%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,"Control","Atg8a-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_length_Atg8a' introuvable###Stats
mod.gen = fitme(log10(Total_Length_mm) ~ Diet * Male_Line + (1 | PhaseRep),data = tab_length_Atg8a)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_Atg8a' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log10(Total_Length_mm) ~ Diet + Male_Line + (1 / PhaseRep),data = tab_length_Atg8a)Error in is.data.frame(data): objet 'tab_length_Atg8a' introuvablemod.gen1 = fitme(log10(Total_Length_mm) ~ Diet + Male_Line + (1 | PhaseRep),data = tab_length_Atg8a)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_Atg8a' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Interaction control vs interaction Atg8a-IR")),
Male_Line = as.character("Atg8a-IR"),
Rep = nlevels(tab_length_Atg8a$PhaseRep),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[4],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))%>%
mutate(Male_Line=fct_relevel(Male_Line,"Atg8a-IR"))Error in levels(x): objet 'tab_length_Atg8a' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison","Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log10(Total_Length_mm) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Variable", "Replicates", : objet 'tab_stat' introuvabletab_stat7K = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_length_Atg8a$Female_Line = factor(tab_length_Atg8a$Female_Line, labels = c(expression(italic(paste("My",o^{TS},">",sep="")))))Error in factor(tab_length_Atg8a$Female_Line, labels = c(expression(italic(paste("My", : objet 'tab_length_Atg8a' introuvablez = max(tab_length_Atg8a$Total_Length_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_length_Atg8a' introuvablePlot_Fig7K=
ggplot(tab_length_Atg8a, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.3, label = paste("(",Sample_size,")",sep="")),size=3)+
facet_grid(.~Male_Line)+
scale_fill_manual(values=cbbHY_HYtoHS)+
scale_x_discrete("",
limits=c("HY","HYtoHS"),
labels=c("HY","HY to HS"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,7.5),
breaks=seq(2,7,by=1))+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_Atg8a, aes(x = Diet, y = Total_Length_mm)): objet 'tab_length_Atg8a' introuvablePlot_Fig7KError in eval(expr, envir, enclos): objet 'Plot_Fig7K' introuvableBlocking Atg2 expression with RNAi in ECs (MyoTS> UAS-Atg2-IR) results in less width shrinkage compared to control midguts. Complete statistical annotation in manuscript’s figure.
tab_length_Atg2 =
d[["7L"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Width_mm=Total.W/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,"Control","Atg2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_length_Atg2%>%
group_by(Diet,Male_Line)%>%
summarise(Sample_size=n())%>%
as.data.frame()%>%
mutate(Male_Line=fct_relevel(Male_Line,"Control","Atg2-IR"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_length_Atg2' introuvable###Stats
mod.gen = fitme(log10(Total_Width_mm) ~ Diet * Male_Line + (1 | PhaseRep),data = tab_length_Atg2)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_Atg2' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log10(Total_Width_mm) ~ Diet + Male_Line + (1 / PhaseRep),data = tab_length_Atg2)Error in is.data.frame(data): objet 'tab_length_Atg2' introuvablemod.gen1 = fitme(log10(Total_Width_mm) ~ Diet + Male_Line + (1 | PhaseRep),data = tab_length_Atg2)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_length_Atg2' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Interaction control vs interaction Atg2-IR")),Male_Line = as.character("Atg2-IR"),
Rep = nlevels(tab_length_Atg2$PhaseRep),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[4],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))%>%
mutate(Male_Line=fct_relevel(Male_Line,"Atg2-IR"))Error in levels(x): objet 'tab_length_Atg2' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log10(Total_width_mm) ~ Diet + Genotype + Diet : Genotype + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Variable", "Replicates", : objet 'tab_stat' introuvabletab_stat7L = tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvable### Plot
tab_length_Atg2$Female_Line = factor(tab_length_Atg2$Female_Line, labels = c(expression(italic(paste("My",o^{TS},">",sep="")))))Error in factor(tab_length_Atg2$Female_Line, labels = c(expression(italic(paste("My", : objet 'tab_length_Atg2' introuvablez = max(tab_length_Atg2$Total_Width_mm, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_length_Atg2' introuvablePlot_Fig7L=
ggplot(tab_length_Atg2, aes(x = Diet, y = Total_Width_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/60) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 0.24, label = paste("(",Sample_size,")",sep="")),size=3)+
# geom_text(data = tab_stat, mapping = aes(x = 1.5, y =0.88, label = paste("p=",Pvalue)),size=3)+
facet_grid(.~Male_Line)+
scale_fill_manual(values=cbbHY_HYtoHS)+
scale_x_discrete("",
limits=c("HY","HYtoHS"),
labels=c("HY","HY to HS"))+
scale_y_continuous("Midgut width (mm)",
limits=c(0.2,0.9),
breaks=seq(0.2,1,by=0.1))+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face="italic", margin = margin(t = 1, r = 0, b = 1, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_length_Atg2, aes(x = Diet, y = Total_Width_mm)): objet 'tab_length_Atg2' introuvablePlot_Fig7LError in eval(expr, envir, enclos): objet 'Plot_Fig7L' introuvable##Export Figure 7
The midgut plastically resizes through changes in EC cell size. Quantification of EC area shows that, in addition to total length, the midgut is also able to plastically resize (Figure 4A) its own ECs. ECs scored are derived from midguts measured for length in figure 4A. Letters above violin plots represent grouping by statistical differences (Post hoc Tukey on GLMM).
tab_area_plasticity =
d[["7 - S1A"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_area_plasticity%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_area_plasticity' introuvable###Stats
mod.gen = fitme(log10(Area) ~ Diet + (1 | Repeat), data = tab_area_plasticity)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_area_plasticity' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log10(Area) ~ Diet + (1 / Repeat), data = tab_area_plasticity) Error in is.data.frame(data): objet 'tab_area_plasticity' introuvablemod.gen1 = fitme(log10(Area) ~ 1 + (1 | Repeat), data = tab_area_plasticity) Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_area_plasticity' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Anova between diets")),
Rep = nlevels(tab_area_plasticity$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=2),
estimate = format(format(mod.gen$fixef[2],digits=3),digits=2),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2,scientific=T)))Error in levels(x): objet 'tab_area_plasticity' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Variable", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log10(Cell area) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Variable", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvablemod.gen = lmer(log10(Area) ~ Diet + (1 | Repeat), data = tab_area_plasticity)Error: bad 'data': objet 'tab_area_plasticity' introuvablemultcomp = glht(mod.gen, linfct=mcp(Diet="Tukey"))Error in model.matrix(model) : objet 'mod.gen' introuvableError in factor_contrasts(model): no 'model.matrix' method for 'model' found!tmp = cld(multcomp)Error in cld(multcomp): objet 'multcomp' introuvableletter_position = aggregate(data=tab_area_plasticity,I(Area/1000) ~ Diet, max)Error in eval(m$data, parent.frame()): objet 'tab_area_plasticity' introuvabletab_letter = as.data.frame(tmp$mcletters$Letters)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tmp' introuvabletab_letter$Diet=rownames(tab_letter)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'rownames' : objet 'tab_letter' introuvablecolnames(tab_letter)[1] = "Letter"Error in colnames(tab_letter)[1] = "Letter": objet 'tab_letter' introuvabletab_letter = left_join(tab_letter,letter_position)Error in left_join(tab_letter, letter_position): objet 'tab_letter' introuvablecolnames(tab_letter)[3] = "Area"Error in colnames(tab_letter)[3] = "Area": objet 'tab_letter' introuvable### Plot
z = max(tab_area_plasticity$Area/1000, na.rm = TRUE)Error in eval(expr, envir, enclos): objet 'tab_area_plasticity' introuvablePlot_Fig7S1A=
ggplot(tab_area_plasticity, aes(x = Diet, y = Area/1000))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = z/300) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -0.01, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_text(data = tab_stat, mapping = aes(x = 1, y =1.15, label = paste("p< ",format(.Machine$double.xmin,digits=2))),size=3)+
geom_text(data = tab_letter, mapping = aes(x = Diet, y = Area+0.05, label = Letter),size=3)+
scale_fill_manual(limits=c("Eclosion", "HY", "HYtoHS", "HYtoHStoHY"),
values= cbbPalette_4 )+
scale_x_discrete("",
limits=c("Eclosion", "HY", "HYtoHS", "HYtoHStoHY"),
labels=c("Eclosion", "HY", "HY to HS", "HY to HS to HY"))+
scale_y_continuous(expression(paste("EC area (10"^3, "mm"^2,")",sep="")),
limits=c(-0.01,1.22),
breaks=seq(0,1.2,by=0.1))+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(
panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=15,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA))Error in ggplot(tab_area_plasticity, aes(x = Diet, y = Area/1000)): objet 'tab_area_plasticity' introuvablePlot_Fig7S1AError in eval(expr, envir, enclos): objet 'Plot_Fig7S1A' introuvableChanges in EC area between HS and HY (ratio HY/HS of mean EC area) significantly correlate with changes in midgut size between HS and HY (ratio HY/HS of mean midgut length) across selected DGRP lines.
tab_corr_length_cell_DGRP_mean_area =
tab_corr_length_cell_DGRP%>%
group_by(ral,diet)%>%
summarise(mean_area=mean(ec.area,na.rm=T))%>%
spread(diet,mean_area)%>%
dplyr::rename(mean_area_HS=HS,
mean_area_HY=HY)%>%
mutate(Ratio_area = mean_area_HY/mean_area_HS)Error in group_by(., ral, diet): objet 'tab_corr_length_cell_DGRP' introuvabletab_corr_length_cell_DGRP_mean_length =
tab_corr_length_cell_DGRP%>%
group_by(ral,diet)%>%
summarise(mean_length=mean(len,na.rm=T))%>%
spread(diet,mean_length)%>%
dplyr::rename(mean_length_HS=HS,
mean_length_HY=HY)%>%
mutate(Ratio_length = mean_length_HY/mean_length_HS)Error in group_by(., ral, diet): objet 'tab_corr_length_cell_DGRP' introuvabletab_corr_length_cell_DGRP_mean= left_join(tab_corr_length_cell_DGRP_mean_length,tab_corr_length_cell_DGRP_mean_area)Error in left_join(tab_corr_length_cell_DGRP_mean_length, tab_corr_length_cell_DGRP_mean_area): objet 'tab_corr_length_cell_DGRP_mean_length' introuvabletab_corr_length_cell_DGRP_mean=as.data.frame(tab_corr_length_cell_DGRP_mean)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.data.frame' : objet 'tab_corr_length_cell_DGRP_mean' introuvablelevels(tab_corr_length_cell_DGRP_mean$ral) <- c("Ral 356", "Ral 362", "Ral 370", "Ral 502", "Ral 765", "Ral 853", "Ral 911" )Error in levels(tab_corr_length_cell_DGRP_mean$ral) <- c("Ral 356", "Ral 362", : objet 'tab_corr_length_cell_DGRP_mean' introuvabletest =
with(tab_corr_length_cell_DGRP_mean,
cor.test(Ratio_area,Ratio_length,method="pearson"))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'data' lors de la s�lection d'une m�thode pour la fonction 'with' : objet 'tab_corr_length_cell_DGRP_mean' introuvabletab_stat = data.frame(Statistic = test$statistic,
cor = test$estimate,
Pvalue = test$p.value)Error in test$statistic: objet de type 'closure' non indiçable#levels(tab_corr_length_cell_DGRP_mean$ral) <- c("Ral 356", "Ral 362", "Ral 370", "Ral 502", "Ral 765", "Ral 853", "Ral 911" )
Plot_Fig7S1B =
ggplot(tab_corr_length_cell_DGRP_mean,aes(x=Ratio_area,y=Ratio_length,label=ral))+
geom_point()+
scale_x_continuous(expression(paste("Ratio HY/HS (mean EC area)")),
limits=c(0.8,2.6),
breaks=c(seq(0.8,2.8,by=0.2)))+
scale_y_continuous("Ratio HY/HS (mean midgut length)",
limits=c(0.8,2.6),
breaks=c(seq(0.8,2.8,by=0.2)))+
geom_text_repel(data=tab_corr_length_cell_DGRP_mean,size=3)+
geom_smooth(method="lm")+
geom_text(data = tab_stat, mapping = aes(x = 1.7, y = 1.7, label = paste("cor=", format(cor, digits=2), "p=",format(Pvalue,digits=2))),size=3)+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
(panel.border = element_blank()),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_blank(),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "horizontal",
legend.box = "horizontal",
legend.position = c(0.25,0.98),
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.4, "cm"),
legend.title = element_blank(),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=Smallfont),
legend.background = element_rect(fill=NA))+
guides(color=guide_legend(ncol=3))Error in ggplot(tab_corr_length_cell_DGRP_mean, aes(x = Ratio_area, y = Ratio_length, : objet 'tab_corr_length_cell_DGRP_mean' introuvablePlot_Fig7S1BError in eval(expr, envir, enclos): objet 'Plot_Fig7S1B' introuvable##Export Figure 7S1
A reporter line for Foxo pathway activity, thor-lacZ, has increased intensity on HS (A, A’) compared to HY (B, B’). Quantification of mean pixel intensity of thor-lacZ stain (C). Complete graphical annotation can be found in manuscript figures
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7- S2A.jpg") Error in transpose(y): object is NULLgob_imageFig7S2A = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7S2A)Error in grid.draw(gob_imageFig7S2A): objet 'gob_imageFig7S2A' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7- S2A1.jpg") Error in transpose(y): object is NULLgob_imageFig7S2A1 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7S2A1)Error in grid.draw(gob_imageFig7S2A1): objet 'gob_imageFig7S2A1' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7- S2B.jpg") Error in transpose(y): object is NULLgob_imageFig7S2B = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7S2B)Error in grid.draw(gob_imageFig7S2B): objet 'gob_imageFig7S2B' introuvableimg = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7- S2B1.jpg") Error in transpose(y): object is NULLgob_imageFig7S2B1 = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7S2B1)Error in grid.draw(gob_imageFig7S2B1): objet 'gob_imageFig7S2B1' introuvableQuantification thor-lacZ
tab_ThorlacZ_rev =
d[["7 - S2C"]]%>%
mutate_if(is.character,as.factor)%>%
mutate_if(is.integer,as.factor)%>%
dplyr::rename(ThorlacZ_int=Mean)Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_ThorlacZ_rev%>%
group_by(Diet)%>%
summarise(Sample_size=n())Error in group_by(., Diet): objet 'tab_ThorlacZ_rev' introuvable###Stats
mod.gen = fitme(log(ThorlacZ_int) ~ Diet + (1 | Repeat),data = tab_ThorlacZ_rev)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_ThorlacZ_rev' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(ThorlacZ_int) ~ Diet + (1 / Repeat),data = tab_ThorlacZ_rev)Error in is.data.frame(data): objet 'tab_ThorlacZ_rev' introuvablemod.gen1 = fitme(log(ThorlacZ_int) ~ 1 + (1 | Repeat),data = tab_ThorlacZ_rev)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_ThorlacZ_rev' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("HS vs HY")),
Rep = nlevels(tab_ThorlacZ_rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_ThorlacZ_rev' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Thor-lacZ intensity) ~ Diet + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvable### Plot
Plot_Fig7S2C=
ggplot(tab_ThorlacZ_rev, aes(x = Diet, y = ThorlacZ_int))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.8) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = -3, label = paste("(",Sample_size,")",sep="")),size=3)+
geom_signif(annotation = formatC(paste("p=",tab_stat$Pvalue), digits = 2), textsize = 3, y_position = 32, xmin = 1, xmax = 2, tip_length = c(0.02, 0.02), vjust = -0.2)+
scale_fill_manual(limits=c("HS","HY"),
values=c("#FFB4B4","#C3E6FC"))+
scale_x_discrete("",
limits=c("HS","HY"),
labels=c("HS","HY"))+
scale_y_continuous(bquote(atop("Mean pixel intensity" ,~ italic (Thor-lacZ) ~ "(a.u.)")),
limits=c(-5,35),
breaks=seq(0,30,by=10))+
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
scale_color_manual(values = palette_mean) +
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black"),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text = element_text(size =Smallfont-2, colour = "black",face="italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_ThorlacZ_rev, aes(x = Diet, y = ThorlacZ_int)): objet 'tab_ThorlacZ_rev' introuvablePlot_Fig7S2CError in eval(expr, envir, enclos): objet 'Plot_Fig7S2C' introuvableBlocking TOR in ECs (5966GS> UAS-Tor-IR) inhibits diet induced midgut growth. For control we used flies of the same genotype but not exposed to RU486. Statistical analyses were performed by comparing interaction between diet and fly line.
tab_5966TOR_rev =
d[["7 - S2D"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
mutate(Treatment=fct_relevel(Treatment,"Ethanol","RU486"))Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_5966TOR_rev%>%
group_by(Diet,Treatment)%>%
summarise(Sample_size=n())Error in group_by(., Diet, Treatment): objet 'tab_5966TOR_rev' introuvable###Stats
mod.gen = fitme(log(Total_Length_mm) ~ Diet * Treatment + (1 | Repeat),data =tab_5966TOR_rev)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_5966TOR_rev' introuvableshapiro.test(residuals(mod.gen)) Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log(Total_Length_mm) ~ Diet + Treatment + (1 / Repeat),data =tab_5966TOR_rev)Error in is.data.frame(data): objet 'tab_5966TOR_rev' introuvablemod.gen1 = fitme(log(Total_Length_mm) ~ Diet + Treatment + (1 | Repeat),data =tab_5966TOR_rev)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_5966TOR_rev' introuvabletest = anova(mod.gen, mod.gen1) Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvableChi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Variable = as.character(paste("Interaction ethanol vs interaction RU486")),
Rep = nlevels(tab_5966TOR_rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=2)))Error in levels(x): objet 'tab_5966TOR_rev' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison", "Replicates", "Chi2","Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>% add_header_above(c("log(Total_Length_mm) ~ Diet + Treatment + Diet : Treatment + (1 | Repeat)" = 8))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Replicates", "Chi2", "Intercept", : objet 'tab_stat' introuvabletab_stat_rev_RU486=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_rev_RU486$Treatment="RU486"Error in tab_stat_rev_RU486$Treatment = "RU486": objet 'tab_stat_rev_RU486' introuvabletab_stat_rev_RU486$Treatment=as.factor(tab_stat_rev_RU486$Treatment)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_stat_rev_RU486' introuvable### Plot
Plot_Fig7S2D =
ggplot(tab_5966TOR_rev, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.11) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.2, label = paste("(",Sample_size,")",sep="")),size=3)+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18,aes(group=Repeat, colour = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
facet_grid(.~ Treatment)+
scale_fill_manual(values=cbbHS_HStoHY)+
scale_x_discrete("",
limits=c("HS D0","HStoHY D7"),
labels=c("HS","HS to HY"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,7),
breaks=seq(2,7,by=1))+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_5966TOR_rev, aes(x = Diet, y = Total_Length_mm)): objet 'tab_5966TOR_rev' introuvablePlot_Fig7S2DError in eval(expr, envir, enclos): objet 'Plot_Fig7S2D' introuvableBlocking autophagy in ECs reduces midgut resizing upon shrinkage (HY to HS for 7 days) using 5966GS> UAS-Atg8a-IR. For control we used flies of the same genotype but not exposed to RU486. Statistical analyses were performed by comparing interaction between diet and fly line. Complete statistical annotation can be found in manuscript’s figure.
tab_5966atg8a_rev =
d[["7 - S2E"]]%>%
mutate_at(vars(!starts_with("Total")),as.factor)%>%
mutate(Total_Length_mm=Total.L/1000)%>%
dplyr::rename(Day_of_treatment=Day,
Female_Line=Female.Line,
Male_Line=Male.Line)%>%
mutate(Treatment=fct_relevel(Treatment,"Ethanol","RU486"))Error in UseMethod("tbl_vars"): pas de méthode pour 'tbl_vars' applicable pour un objet de classe "NULL"Sample_size=
tab_5966atg8a_rev%>%
group_by(Male_Line,Diet,Treatment)%>%
summarise(Sample_size=n())Error in group_by(., Male_Line, Diet, Treatment): objet 'tab_5966atg8a_rev' introuvable###Stats
mod.gen = fitme(log10(Total_Length_mm) ~ Diet * Treatment + (1 | Repeat),data = tab_5966atg8a_rev)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_5966atg8a_rev' introuvableshapiro.test(residuals(mod.gen))Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'object' lors de la s�lection d'une m�thode pour la fonction 'residuals' : objet 'mod.gen' introuvablebptest(log10(Total_Length_mm) ~ Diet * Treatment + (1 / Repeat),data = tab_5966atg8a_rev)Error in is.data.frame(data): objet 'tab_5966atg8a_rev' introuvablemod.gen1 = fitme(log10(Total_Length_mm) ~ Diet + Treatment + (1 | Repeat),data = tab_5966atg8a_rev)Error in (function (control.HLfit, ranFix = NULL, HLmethod, predictor, : objet 'tab_5966atg8a_rev' introuvabletest = anova(mod.gen, mod.gen1)Error in anova(mod.gen, mod.gen1): objet 'mod.gen' introuvabletestfunction (pkg = ".", filter = NULL, stop_on_failure = FALSE,
export_all = TRUE, ...)
{
save_all()
pkg <- as.package(pkg)
if (!uses_testthat(pkg) && interactive()) {
cli::cli_alert_danger("No testing infrastructure found. Create it?")
if (utils::menu(c("Yes", "No")) == 1) {
usethis_use_testthat(pkg)
}
return(invisible())
}
load_all(pkg$path)
cli::cli_alert_info("Testing {.pkg {pkg$package}}")
withr::local_envvar(r_env_vars())
testthat::test_local(pkg$path, filter = filter, stop_on_failure = stop_on_failure,
...)
}
<bytecode: 0x000000009e53be20>
<environment: namespace:devtools>Chi2_LRT_growth = 2*(mod.gen$APHLs[["p_v"]]-mod.gen1$APHLs[["p_v"]])Error in eval(expr, envir, enclos): objet 'mod.gen' introuvabletab_stat = data.frame(Comparison = as.character(paste("Interaction ethanol vs interaction RU486")),
Male_Line = as.character(paste("Atg8a-IR")),
Rep = nlevels(tab_5966atg8a_rev$Repeat),
chi2_LR = round(as.numeric(test$basicLRT$chi2_LR), digits = 2),
intercept = format(mod.gen$fixef[1],digits=3),
estimate = format(mod.gen$fixef[2],digits=3),
df = as.numeric(test$basicLRT$df),
Pvalue = as.numeric(format(pchisq(Chi2_LRT_growth,df=1,lower.tail = F),digits=1,scientific=F)))Error in levels(x): objet 'tab_5966atg8a_rev' introuvabletab_stat$sig = ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*",
ifelse(tab_stat$Pvalue < 0.01 & tab_stat$Pvalue > 0.001, "**",
ifelse(tab_stat$Pvalue < 0.001, "***", "")))Error in ifelse(tab_stat$Pvalue < 0.05 & tab_stat$Pvalue > 0.01, "*", : objet 'tab_stat' introuvabletab_stat%>%
kable(col.names = c("Comparison","Variable", "Replicates", "Chi2", "Intercept","Estimate","df" ,"p-value","Signif."),row.names = FALSE) %>%
add_header_above(c("log(Total_Length_mm) ~ Diet + Treatment + Diet : Treatment + (1 | Repeat)" = 9))%>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = F)Error in kable(., col.names = c("Comparison", "Variable", "Replicates", : objet 'tab_stat' introuvabletab_stat_5966atg8a_rev=tab_statError in eval(expr, envir, enclos): objet 'tab_stat' introuvabletab_stat_5966atg8a_rev$Treatment="RU486"Error in tab_stat_5966atg8a_rev$Treatment = "RU486": objet 'tab_stat_5966atg8a_rev' introuvabletab_stat_5966atg8a_rev$Treatment=as.factor(tab_stat_rev_RU486$Treatment)Error in h(simpleError(msg, call)): erreur d'�valuation de l'argument 'x' lors de la s�lection d'une m�thode pour la fonction 'as.factor' : objet 'tab_stat_rev_RU486' introuvable### Plot
Plot_Fig7S2E =
ggplot(tab_5966atg8a_rev, aes(x = Diet, y = Total_Length_mm))+
geom_violin(aes(fill = Diet), draw_quantiles = c(0.25, 0.5, 0.75), colour = "black", size = 0.2,adjust = 0.8) +
geom_dotplot( colour = "black", fill = "white", binaxis = "y", stackdir = "center", binwidth = 0.11) +
geom_text(data = Sample_size, mapping = aes(x = Diet, y = 2.2, label = paste("(",Sample_size,")",sep="")),size=3)+
stat_summary(fun = mean, geom = "point", size = 2, shape = 18,aes(group=Repeat, colour = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 3, shape = 18, colour = "black", aes(group = Repeat)) +
stat_summary(fun = mean, geom = "point", size = 2, shape = 18, aes(group = Repeat, colour = Repeat)) +
stat_summary(fun = mean, colour = "black", geom = "line", aes(group = Repeat)) +
scale_color_manual(values = palette_mean) +
facet_grid(~ Treatment)+
scale_fill_manual(values=cbbHY_HYtoHS)+
scale_x_discrete("",
limits=c("HY","HYtoHS"),
labels=c("HY","HY to HS"))+
scale_y_continuous("Midgut length (mm)",
limits=c(2,8),
breaks=seq(2,8,by=1))+
theme(panel.grid.major.y = element_line(colour = grey(0.45), linetype = "dashed", size = 0.2),
panel.background = element_blank(),
axis.title.x = element_text(size=Smallfont,colour="black"),
axis.title.y = element_text(size=Smallfont,colour="black"),
axis.line.x = element_line(colour="black",size=0.75),
axis.line.y = element_line(colour="black",size=0.75),
axis.ticks.x = element_line(size = 0.75),
axis.ticks.y = element_line(size = 0.75),
axis.text.x = element_text(size=Smallfont,colour="black",angle=30,hjust=1),
axis.text.y = element_text(size=Smallfont,colour="black"),
plot.margin = unit(Margin, "cm"),
legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "none",
legend.key.height = unit(0.4, "cm"),
legend.key.width= unit(0.6, "cm"),
legend.title = element_text(face="italic",size=Smallfont),
legend.key = element_rect(colour = 'white', fill = "white", linetype='dashed'),
legend.text = element_text(size=SuperSmallfont),
legend.background = element_rect(fill=NA),
strip.text.x = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.text.y = element_text(size = Smallfont, colour = "black", face = "italic", margin = margin(t = 2, r = 0, b = 2, l = 0)),
strip.background = element_rect(fill=NA, colour="black"),
strip.placement="outside")Error in ggplot(tab_5966atg8a_rev, aes(x = Diet, y = Total_Length_mm)): objet 'tab_5966atg8a_rev' introuvablePlot_Fig7S2EError in eval(expr, envir, enclos): objet 'Plot_Fig7S2E' introuvable##Export Figure 7S2
Scheme depicting the regulation of midgut size in response to dietary changes. EC size, together with the balance between cell gain and cell loss, determine midgut size. Diet can influence these three parameters, thus influencing midgut size. Yeast promotes midgut growth, and sugar antagonizes it. Sugar inhibits translation and uncouples ISC proliferation from expression of stress-derived pro-mitotic signals, thus resulting in smaller guts.
img = readImage("F:/Dropbox/Github/Bonfini_eLife_2021/data/7 - S3A.jpg") Error in transpose(y): object is NULLgob_imageFig7S3A = rasterGrob(img)Error in UseMethod("as.raster"): pas de méthode pour 'as.raster' applicable pour un objet de classe "list"grid.draw(gob_imageFig7S3A)Error in grid.draw(gob_imageFig7S3A): objet 'gob_imageFig7S3A' introuvable##Export Figure 7S3
sessionInfo()R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19043)
Matrix products: default
locale:
[1] LC_COLLATE=French_France.1252 LC_CTYPE=French_France.1252
[3] LC_MONETARY=French_France.1252 LC_NUMERIC=C
[5] LC_TIME=French_France.1252
attached base packages:
[1] parallel stats4 grid stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] ggsignif_0.6.2 plotfunctions_1.4
[3] kableExtra_1.3.4 knitr_1.33
[5] ggplotify_0.1.0 coxme_2.2-16
[7] bdsmatrix_1.3-4 DESeq2_1.32.0
[9] SummarizedExperiment_1.22.0 Biobase_2.52.0
[11] MatrixGenerics_1.4.3 matrixStats_0.60.1
[13] GenomicRanges_1.44.0 GenomeInfoDb_1.28.0
[15] IRanges_2.26.0 S4Vectors_0.30.0
[17] BiocGenerics_0.38.0 ggh4x_0.2.0
[19] forcats_0.5.1 metR_0.11.0
[21] ggrepel_0.9.1 multcomp_1.4-17
[23] TH.data_1.0-10 mvtnorm_1.1-2
[25] gridGraphics_0.5-1 RColorBrewer_1.1-2
[27] gplots_3.1.1 EBImage_4.34.0
[29] fields_12.5 viridis_0.6.1
[31] viridisLite_0.4.0 spam_2.7-0
[33] dotCall64_1.0-1 lme4_1.1-27.1
[35] Matrix_1.3-3 spaMM_3.8.0
[37] data.table_1.14.0 phia_0.2-1
[39] tidyr_1.1.3 scales_1.1.1
[41] stringr_1.4.0 dplyr_1.0.7
[43] xlsx_0.6.5 xlsxjars_0.6.1
[45] rJava_1.0-5 doBy_4.6.10
[47] psych_2.1.6 nparLD_2.1
[49] agricolae_1.3-5 gridExtra_2.3
[51] plotrix_3.8-1 survival_3.2-11
[53] ggplot2_3.3.5 lmtest_0.9-38
[55] zoo_1.8-9 car_3.0-10
[57] carData_3.0-4 MASS_7.3-54
[59] lattice_0.20-44 reshape2_1.4.4
[61] devtools_2.4.2 usethis_2.0.1
[63] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] bit64_4.0.5 DelayedArray_0.18.0 KEGGREST_1.32.0
[4] RCurl_1.98-1.3 generics_0.1.0 callr_3.7.0
[7] RSQLite_2.2.7 combinat_0.0-8 proxy_0.4-26
[10] bit_4.0.4 webshot_0.5.2 xml2_1.3.2
[13] lubridate_1.7.10 httpuv_1.6.1 assertthat_0.2.1
[16] xfun_0.24 hms_1.1.0 jquerylib_0.1.4
[19] evaluate_0.14 promises_1.2.0.1 fansi_0.5.0
[22] caTools_1.18.2 readxl_1.3.1 DBI_1.1.1
[25] geneplotter_1.70.0 tmvnsim_1.0-2 htmlwidgets_1.5.3
[28] purrr_0.3.4 ellipsis_0.3.2 backports_1.2.1
[31] annotate_1.70.0 ROI_1.0-0 vctrs_0.3.8
[34] remotes_2.4.1 abind_1.4-5 cachem_1.0.5
[37] withr_2.4.2 checkmate_2.0.0 prettyunits_1.1.1
[40] mnormt_2.0.2 svglite_2.0.0 cluster_2.1.2
[43] crayon_1.4.1 genefilter_1.74.0 pkgconfig_2.0.3
[46] slam_0.1-48 nlme_3.1-152 pkgload_1.2.2
[49] rlang_0.4.11 questionr_0.7.4 lifecycle_1.0.0
[52] miniUI_0.1.1.1 sandwich_3.0-1 registry_0.5-1
[55] cellranger_1.1.0 rprojroot_2.0.2 tiff_0.1-8
[58] boot_1.3-28 whisker_0.4 processx_3.5.2
[61] png_0.1-7 bitops_1.0-7 KernSmooth_2.23-20
[64] Biostrings_2.60.1 blob_1.2.1 jpeg_0.1-8.1
[67] klaR_0.6-15 memoise_2.0.0 magrittr_2.0.1
[70] plyr_1.8.6 zlibbioc_1.38.0 compiler_4.1.0
[73] cli_3.0.1 XVector_0.32.0 pbapply_1.4-3
[76] ps_1.6.0 tidyselect_1.1.1 stringi_1.6.2
[79] highr_0.9 yaml_2.2.1 locfit_1.5-9.4
[82] sass_0.4.0 tools_4.1.0 rio_0.5.27
[85] rstudioapi_0.13 foreign_0.8-81 git2r_0.28.0
[88] digest_0.6.27 shiny_1.6.0 Rcpp_1.0.7
[91] microbenchmark_1.4-7 broom_0.7.8 later_1.2.0
[94] httr_1.4.2 AnnotationDbi_1.54.1 Deriv_4.1.3
[97] colorspace_2.0-2 rvest_1.0.0 XML_3.99-0.6
[100] fs_1.5.0 splines_4.1.0 yulab.utils_0.0.2
[103] sessioninfo_1.1.1 systemfonts_1.0.2 xtable_1.8-4
[106] jsonlite_1.7.2 nloptr_1.2.2.2 AlgDesign_1.2.0
[109] testthat_3.1.0 R6_2.5.0 pillar_1.6.1
[112] htmltools_0.5.1.1 mime_0.11 glue_1.4.2
[115] fastmap_1.1.0 minqa_1.2.4 BiocParallel_1.26.2
[118] fftwtools_0.9-11 codetools_0.2-18 maps_3.3.0
[121] pkgbuild_1.2.0 utf8_1.2.1 bslib_0.2.5.1
[124] tibble_3.1.2 numDeriv_2016.8-1.1 curl_4.3.2
[127] gtools_3.9.2 zip_2.2.0 openxlsx_4.2.4
[130] rmarkdown_2.9 desc_1.4.0 curry_0.1.1
[133] munsell_0.5.0 GenomeInfoDbData_1.2.6 labelled_2.8.0
[136] haven_2.4.1 gtable_0.3.0