Figure 3 Analysis
Last updated: 2026-01-06
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Knit directory: DXR_website/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | c382b38 | emmapfort | 2026-01-06 | Build site. |
| html | 7f22593 | emmapfort | 2026-01-05 | Build site. |
| Rmd | 49fa865 | emmapfort | 2026-01-05 | Final Updates to Website EMP 01/05/26 |
| Rmd | a967d53 | emmapfort | 2025-12-09 | Update website and analysis chunks |
| Rmd | da1f69c | emmapfort | 2025-12-02 | updated analysis 12/02/25 |
Libraries
Load necessary libraries for analysis.
library(tidyverse)
library(readxl)
library(readr)
library(ggVennDiagram)
library(ggrastr)
library(eulerr)
library(ggfortify)
library(gprofiler2)
library(edgeR)Define my custom plot theme
# Define the custom theme
# plot_theme_custom <- function() {
# theme_minimal() +
# theme(
# #line for x and y axis
# axis.line = element_line(linewidth = 1,
# color = "black"),
#
# #axis ticks only on x and y, length standard
# axis.ticks.x = element_line(color = "black",
# linewidth = 1),
# axis.ticks.y = element_line(color = "black",
# linewidth = 1),
# axis.ticks.length = unit(0.05, "in"),
#
# #text and font
# axis.text = element_text(color = "black",
# family = "Arial",
# size = 7),
# axis.title = element_text(color = "black",
# family = "Arial",
# size = 9),
# legend.text = element_text(color = "black",
# family = "Arial",
# size = 7),
# legend.title = element_text(color = "black",
# family = "Arial",
# size = 9),
# plot.title = element_text(color = "black",
# family = "Arial",
# size = 10),
#
# #blank background and border
# panel.background = element_blank(),
# panel.border = element_blank(),
#
# #gridlines for alignment
# panel.grid.major = element_line(color = "grey80", linewidth = 0.5), #grey major grid for align in illus
# panel.grid.minor = element_line(color = "grey90", linewidth = 0.5) #grey minor grid for align in illus
# )
# }
# saveRDS(plot_theme_custom, "data/plot_theme_custom.RDS")
theme_custom <- readRDS("data/plot_theme_custom.RDS")Define a function to save plots as .pdf and .png
save_plot <- function(plot, filename,
folder = ".",
width = 8,
height = 6,
units = "in",
dpi = 300,
add_date = TRUE) {
if (missing(filename)) stop("Please provide a filename (without extension) for the plot.")
date_str <- if (add_date) paste0("_", format(Sys.Date(), "%y%m%d")) else ""
pdf_file <- file.path(folder, paste0(filename, date_str, ".pdf"))
png_file <- file.path(folder, paste0(filename, date_str, ".png"))
ggsave(filename = pdf_file, plot = plot, device = cairo_pdf, width = width, height = height, units = units, bg = "transparent")
ggsave(filename = png_file, plot = plot, device = "png", width = width, height = height, units = units, dpi = dpi, bg = "transparent")
message("Saved plot as Cairo PDF: ", pdf_file)
message("Saved plot as PNG: ", png_file)
}
output_folder <- "C:/Users/emmap/OneDrive/Desktop/DXR Manuscript Materials/Fig pdfs"
#save plot function created
#to use: just define the plot name, filename_base, width, heightCormotif Function
## Fit limma model using code as it is found in the original cormotif code. It has
## only been modified to add names to the matrix of t values, as well as the
## limma fits
limmafit.default <- function(exprs,groupid,compid) {
limmafits <- list()
compnum <- nrow(compid)
genenum <- nrow(exprs)
limmat <- matrix(0,genenum,compnum)
limmas2 <- rep(0,compnum)
limmadf <- rep(0,compnum)
limmav0 <- rep(0,compnum)
limmag1num <- rep(0,compnum)
limmag2num <- rep(0,compnum)
rownames(limmat) <- rownames(exprs)
colnames(limmat) <- rownames(compid)
names(limmas2) <- rownames(compid)
names(limmadf) <- rownames(compid)
names(limmav0) <- rownames(compid)
names(limmag1num) <- rownames(compid)
names(limmag2num) <- rownames(compid)
for(i in 1:compnum) {
selid1 <- which(groupid == compid[i,1])
selid2 <- which(groupid == compid[i,2])
eset <- new("ExpressionSet", exprs=cbind(exprs[,selid1],exprs[,selid2]))
g1num <- length(selid1)
g2num <- length(selid2)
designmat <- cbind(base=rep(1,(g1num+g2num)), delta=c(rep(0,g1num),rep(1,g2num)))
fit <- lmFit(eset,designmat)
fit <- eBayes(fit)
limmat[,i] <- fit$t[,2]
limmas2[i] <- fit$s2.prior
limmadf[i] <- fit$df.prior
limmav0[i] <- fit$var.prior[2]
limmag1num[i] <- g1num
limmag2num[i] <- g2num
limmafits[[i]] <- fit
# log odds
# w<-sqrt(1+fit$var.prior[2]/(1/g1num+1/g2num))
# log(0.99)+dt(fit$t[1,2],g1num+g2num-2+fit$df.prior,log=TRUE)-log(0.01)-dt(fit$t[1,2]/w, g1num+g2num-2+fit$df.prior, log=TRUE)+log(w)
}
names(limmafits) <- rownames(compid)
limmacompnum<-nrow(compid)
result<-list(t = limmat,
v0 = limmav0,
df0 = limmadf,
s20 = limmas2,
g1num = limmag1num,
g2num = limmag2num,
compnum = limmacompnum,
fits = limmafits)
}
limmafit.counts <-
function (exprs, groupid, compid, norm.factor.method = "TMM", voom.normalize.method = "none")
{
limmafits <- list()
compnum <- nrow(compid)
genenum <- nrow(exprs)
limmat <- matrix(NA,genenum,compnum)
limmas2 <- rep(0,compnum)
limmadf <- rep(0,compnum)
limmav0 <- rep(0,compnum)
limmag1num <- rep(0,compnum)
limmag2num <- rep(0,compnum)
rownames(limmat) <- rownames(exprs)
colnames(limmat) <- rownames(compid)
names(limmas2) <- rownames(compid)
names(limmadf) <- rownames(compid)
names(limmav0) <- rownames(compid)
names(limmag1num) <- rownames(compid)
names(limmag2num) <- rownames(compid)
for (i in 1:compnum) {
message(paste("Running limma for comparision",i,"/",compnum))
selid1 <- which(groupid == compid[i, 1])
selid2 <- which(groupid == compid[i, 2])
# make a new count data frame
counts <- cbind(exprs[, selid1], exprs[, selid2])
# remove NAs
not.nas <- which(apply(counts, 1, function(x) !any(is.na(x))) == TRUE)
# runn voom/limma
d <- DGEList(counts[not.nas,])
d <- calcNormFactors(d, method = norm.factor.method)
g1num <- length(selid1)
g2num <- length(selid2)
designmat <- cbind(base = rep(1, (g1num + g2num)), delta = c(rep(0,
g1num), rep(1, g2num)))
y <- voom(d, designmat, normalize.method = voom.normalize.method)
fit <- lmFit(y, designmat)
fit <- eBayes(fit)
limmafits[[i]] <- fit
limmat[not.nas, i] <- fit$t[, 2]
limmas2[i] <- fit$s2.prior
limmadf[i] <- fit$df.prior
limmav0[i] <- fit$var.prior[2]
limmag1num[i] <- g1num
limmag2num[i] <- g2num
}
limmacompnum <- nrow(compid)
names(limmafits) <- rownames(compid)
result <- list(t = limmat,
v0 = limmav0,
df0 = limmadf,
s20 = limmas2,
g1num = limmag1num,
g2num = limmag2num,
compnum = limmacompnum,
fits = limmafits)
}
limmafit.list <-
function (fitlist, cmp.idx=2)
{
compnum <- length(fitlist)
genes <- c()
for (i in 1:compnum) genes <- unique(c(genes, rownames(fitlist[[i]])))
genenum <- length(genes)
limmat <- matrix(NA,genenum,compnum)
limmas2 <- rep(0,compnum)
limmadf <- rep(0,compnum)
limmav0 <- rep(0,compnum)
limmag1num <- rep(0,compnum)
limmag2num <- rep(0,compnum)
rownames(limmat) <- genes
colnames(limmat) <- names(fitlist)
names(limmas2) <- names(fitlist)
names(limmadf) <- names(fitlist)
names(limmav0) <- names(fitlist)
names(limmag1num) <- names(fitlist)
names(limmag2num) <- names(fitlist)
for (i in 1:compnum) {
this.t <- fitlist[[i]]$t[,cmp.idx]
limmat[names(this.t),i] <- this.t
limmas2[i] <- fitlist[[i]]$s2.prior
limmadf[i] <- fitlist[[i]]$df.prior
limmav0[i] <- fitlist[[i]]$var.prior[cmp.idx]
limmag1num[i] <- sum(fitlist[[i]]$design[,cmp.idx]==0)
limmag2num[i] <- sum(fitlist[[i]]$design[,cmp.idx]==1)
}
limmacompnum <- compnum
result <- list(t = limmat,
v0 = limmav0,
df0 = limmadf,
s20 = limmas2,
g1num = limmag1num,
g2num = limmag2num,
compnum = limmacompnum,
fits = limmafits)
}
## Rank genes based on statistics
generank<-function(x) {
xcol<-ncol(x)
xrow<-nrow(x)
result<-matrix(0,xrow,xcol)
z<-(1:1:xrow)
for(i in 1:xcol) {
y<-sort(x[,i],decreasing=TRUE,na.last=TRUE)
result[,i]<-match(x[,i],y)
result[,i]<-order(result[,i])
}
result
}
## Log-likelihood for moderated t under H0
modt.f0.loglike<-function(x,df) {
a<-dt(x, df, log=TRUE)
result<-as.vector(a)
flag<-which(is.na(result)==TRUE)
result[flag]<-0
result
}
## Log-likelihood for moderated t under H1
## param=c(df,g1num,g2num,v0)
modt.f1.loglike<-function(x,param) {
df<-param[1]
g1num<-param[2]
g2num<-param[3]
v0<-param[4]
w<-sqrt(1+v0/(1/g1num+1/g2num))
dt(x/w, df, log=TRUE)-log(w)
a<-dt(x/w, df, log=TRUE)-log(w)
result<-as.vector(a)
flag<-which(is.na(result)==TRUE)
result[flag]<-0
result
}
## Correlation Motif Fit
cmfit.X<-function(x, type, K=1, tol=1e-3, max.iter=100) {
## initialize
xrow <- nrow(x)
xcol <- ncol(x)
loglike0 <- list()
loglike1 <- list()
p <- rep(1, K)/K
q <- matrix(runif(K * xcol), K, xcol)
q[1, ] <- rep(0.01, xcol)
for (i in 1:xcol) {
f0 <- type[[i]][[1]]
f0param <- type[[i]][[2]]
f1 <- type[[i]][[3]]
f1param <- type[[i]][[4]]
loglike0[[i]] <- f0(x[, i], f0param)
loglike1[[i]] <- f1(x[, i], f1param)
}
condlike <- list()
for (i in 1:xcol) {
condlike[[i]] <- matrix(0, xrow, K)
}
loglike.old <- -1e+10
for (i.iter in 1:max.iter) {
if ((i.iter%%50) == 0) {
print(paste("We have run the first ", i.iter, " iterations for K=",
K, sep = ""))
}
err <- tol + 1
clustlike <- matrix(0, xrow, K)
#templike <- matrix(0, xrow, 2)
templike1 <- rep(0, xrow)
templike2 <- rep(0, xrow)
for (j in 1:K) {
for (i in 1:xcol) {
templike1 <- log(q[j, i]) + loglike1[[i]]
templike2 <- log(1 - q[j, i]) + loglike0[[i]]
tempmax <- Rfast::Pmax(templike1, templike2)
templike1 <- exp(templike1 - tempmax)
templike2 <- exp(templike2 - tempmax)
tempsum <- templike1 + templike2
clustlike[, j] <- clustlike[, j] + tempmax +
log(tempsum)
condlike[[i]][, j] <- templike1/tempsum
}
clustlike[, j] <- clustlike[, j] + log(p[j])
}
#tempmax <- apply(clustlike, 1, max)
tempmax <- Rfast::rowMaxs(clustlike, value=TRUE)
for (j in 1:K) {
clustlike[, j] <- exp(clustlike[, j] - tempmax)
}
#tempsum <- apply(clustlike, 1, sum)
tempsum <- Rfast::rowsums(clustlike)
for (j in 1:K) {
clustlike[, j] <- clustlike[, j]/tempsum
}
#p.new <- (apply(clustlike, 2, sum) + 1)/(xrow + K)
p.new <- (Rfast::colsums(clustlike) + 1)/(xrow + K)
q.new <- matrix(0, K, xcol)
for (j in 1:K) {
clustpsum <- sum(clustlike[, j])
for (i in 1:xcol) {
q.new[j, i] <- (sum(clustlike[, j] * condlike[[i]][,
j]) + 1)/(clustpsum + 2)
}
}
err.p <- max(abs(p.new - p)/p)
err.q <- max(abs(q.new - q)/q)
err <- max(err.p, err.q)
loglike.new <- (sum(tempmax + log(tempsum)) + sum(log(p.new)) +
sum(log(q.new) + log(1 - q.new)))/xrow
p <- p.new
q <- q.new
loglike.old <- loglike.new
if (err < tol) {
break
}
}
clustlike <- matrix(0, xrow, K)
for (j in 1:K) {
for (i in 1:xcol) {
templike1 <- log(q[j, i]) + loglike1[[i]]
templike2 <- log(1 - q[j, i]) + loglike0[[i]]
tempmax <- Rfast::Pmax(templike1, templike2)
templike1 <- exp(templike1 - tempmax)
templike2 <- exp(templike2 - tempmax)
tempsum <- templike1 + templike2
clustlike[, j] <- clustlike[, j] + tempmax + log(tempsum)
condlike[[i]][, j] <- templike1/tempsum
}
clustlike[, j] <- clustlike[, j] + log(p[j])
}
#tempmax <- apply(clustlike, 1, max)
tempmax <- Rfast::rowMaxs(clustlike, value=TRUE)
for (j in 1:K) {
clustlike[, j] <- exp(clustlike[, j] - tempmax)
}
#tempsum <- apply(clustlike, 1, sum)
tempsum <- Rfast::rowsums(clustlike)
for (j in 1:K) {
clustlike[, j] <- clustlike[, j]/tempsum
}
p.post <- matrix(0, xrow, xcol)
for (j in 1:K) {
for (i in 1:xcol) {
p.post[, i] <- p.post[, i] + clustlike[, j] * condlike[[i]][,
j]
}
}
loglike.old <- loglike.old - (sum(log(p)) + sum(log(q) +
log(1 - q)))/xrow
loglike.old <- loglike.old * xrow
result <- list(p.post = p.post, motif.prior = p, motif.q = q,
loglike = loglike.old, clustlike=clustlike, condlike=condlike)
}
## Fit using (0,0,...,0) and (1,1,...,1)
cmfitall<-function(x, type, tol=1e-3, max.iter=100) {
## initialize
xrow<-nrow(x)
xcol<-ncol(x)
loglike0<-list()
loglike1<-list()
p<-0.01
## compute loglikelihood
L0<-matrix(0,xrow,1)
L1<-matrix(0,xrow,1)
for(i in 1:xcol) {
f0<-type[[i]][[1]]
f0param<-type[[i]][[2]]
f1<-type[[i]][[3]]
f1param<-type[[i]][[4]]
loglike0[[i]]<-f0(x[,i],f0param)
loglike1[[i]]<-f1(x[,i],f1param)
L0<-L0+loglike0[[i]]
L1<-L1+loglike1[[i]]
}
## EM algorithm to get MLE of p and q
loglike.old <- -1e10
for(i.iter in 1:max.iter) {
if((i.iter%%50) == 0) {
print(paste("We have run the first ", i.iter, " iterations",sep=""))
}
err<-tol+1
## compute posterior cluster membership
clustlike<-matrix(0,xrow,2)
clustlike[,1]<-log(1-p)+L0
clustlike[,2]<-log(p)+L1
tempmax<-apply(clustlike,1,max)
for(j in 1:2) {
clustlike[,j]<-exp(clustlike[,j]-tempmax)
}
tempsum<-apply(clustlike,1,sum)
## update motif occurrence rate
for(j in 1:2) {
clustlike[,j]<-clustlike[,j]/tempsum
}
p.new<-(sum(clustlike[,2])+1)/(xrow+2)
## evaluate convergence
err<-abs(p.new-p)/p
## evaluate whether the log.likelihood increases
loglike.new<-(sum(tempmax+log(tempsum))+log(p.new)+log(1-p.new))/xrow
loglike.old<-loglike.new
p<-p.new
if(err<tol) {
break;
}
}
## compute posterior p
clustlike<-matrix(0,xrow,2)
clustlike[,1]<-log(1-p)+L0
clustlike[,2]<-log(p)+L1
tempmax<-apply(clustlike,1,max)
for(j in 1:2) {
clustlike[,j]<-exp(clustlike[,j]-tempmax)
}
tempsum<-apply(clustlike,1,sum)
for(j in 1:2) {
clustlike[,j]<-clustlike[,j]/tempsum
}
p.post<-matrix(0,xrow,xcol)
for(i in 1:xcol) {
p.post[,i]<-clustlike[,2]
}
## return
#calculate back loglikelihood
loglike.old<-loglike.old-(log(p)+log(1-p))/xrow
loglike.old<-loglike.old*xrow
result<-list(p.post=p.post, motif.prior=p, loglike=loglike.old)
}
## Fit each dataset separately
cmfitsep<-function(x, type, tol=1e-3, max.iter=100) {
## initialize
xrow<-nrow(x)
xcol<-ncol(x)
loglike0<-list()
loglike1<-list()
p<-0.01*rep(1,xcol)
loglike.final<-rep(0,xcol)
## compute loglikelihood
for(i in 1:xcol) {
f0<-type[[i]][[1]]
f0param<-type[[i]][[2]]
f1<-type[[i]][[3]]
f1param<-type[[i]][[4]]
loglike0[[i]]<-f0(x[,i],f0param)
loglike1[[i]]<-f1(x[,i],f1param)
}
p.post<-matrix(0,xrow,xcol)
## EM algorithm to get MLE of p
for(coli in 1:xcol) {
loglike.old <- -1e10
for(i.iter in 1:max.iter) {
if((i.iter%%50) == 0) {
print(paste("We have run the first ", i.iter, " iterations",sep=""))
}
err<-tol+1
## compute posterior cluster membership
clustlike<-matrix(0,xrow,2)
clustlike[,1]<-log(1-p[coli])+loglike0[[coli]]
clustlike[,2]<-log(p[coli])+loglike1[[coli]]
tempmax<-apply(clustlike,1,max)
for(j in 1:2) {
clustlike[,j]<-exp(clustlike[,j]-tempmax)
}
tempsum<-apply(clustlike,1,sum)
## evaluate whether the log.likelihood increases
loglike.new<-sum(tempmax+log(tempsum))/xrow
## update motif occurrence rate
for(j in 1:2) {
clustlike[,j]<-clustlike[,j]/tempsum
}
p.new<-(sum(clustlike[,2]))/(xrow)
## evaluate convergence
err<-abs(p.new-p[coli])/p[coli]
loglike.old<-loglike.new
p[coli]<-p.new
if(err<tol) {
break;
}
}
## compute posterior p
clustlike<-matrix(0,xrow,2)
clustlike[,1]<-log(1-p[coli])+loglike0[[coli]]
clustlike[,2]<-log(p[coli])+loglike1[[coli]]
tempmax<-apply(clustlike,1,max)
for(j in 1:2) {
clustlike[,j]<-exp(clustlike[,j]-tempmax)
}
tempsum<-apply(clustlike,1,sum)
for(j in 1:2) {
clustlike[,j]<-clustlike[,j]/tempsum
}
p.post[,coli]<-clustlike[,2]
loglike.final[coli]<-loglike.old
}
## return
loglike.final<-loglike.final*xrow
result<-list(p.post=p.post, motif.prior=p, loglike=loglike.final)
}
## Fit the full model
cmfitfull<-function(x, type, tol=1e-3, max.iter=100) {
## initialize
xrow<-nrow(x)
xcol<-ncol(x)
loglike0<-list()
loglike1<-list()
K<-2^xcol
p<-rep(1,K)/K
pattern<-rep(0,xcol)
patid<-matrix(0,K,xcol)
## compute loglikelihood
for(i in 1:xcol) {
f0<-type[[i]][[1]]
f0param<-type[[i]][[2]]
f1<-type[[i]][[3]]
f1param<-type[[i]][[4]]
loglike0[[i]]<-f0(x[,i],f0param)
loglike1[[i]]<-f1(x[,i],f1param)
}
L<-matrix(0,xrow,K)
for(i in 1:K)
{
patid[i,]<-pattern
for(j in 1:xcol) {
if(pattern[j] < 0.5) {
L[,i]<-L[,i]+loglike0[[j]]
} else {
L[,i]<-L[,i]+loglike1[[j]]
}
}
if(i < K) {
pattern[xcol]<-pattern[xcol]+1
j<-xcol
while(pattern[j] > 1) {
pattern[j]<-0
j<-j-1
pattern[j]<-pattern[j]+1
}
}
}
## EM algorithm to get MLE of p and q
loglike.old <- -1e10
for(i.iter in 1:max.iter) {
if((i.iter%%50) == 0) {
print(paste("We have run the first ", i.iter, " iterations",sep=""))
}
err<-tol+1
## compute posterior cluster membership
clustlike<-matrix(0,xrow,K)
for(j in 1:K) {
clustlike[,j]<-log(p[j])+L[,j]
}
tempmax<-apply(clustlike,1,max)
for(j in 1:K) {
clustlike[,j]<-exp(clustlike[,j]-tempmax)
}
tempsum<-apply(clustlike,1,sum)
## update motif occurrence rate
for(j in 1:K) {
clustlike[,j]<-clustlike[,j]/tempsum
}
p.new<-(apply(clustlike,2,sum)+1)/(xrow+K)
## evaluate convergence
err<-max(abs(p.new-p)/p)
## evaluate whether the log.likelihood increases
loglike.new<-(sum(tempmax+log(tempsum))+sum(log(p.new)))/xrow
loglike.old<-loglike.new
p<-p.new
if(err<tol) {
break;
}
}
## compute posterior p
clustlike<-matrix(0,xrow,K)
for(j in 1:K) {
clustlike[,j]<-log(p[j])+L[,j]
}
tempmax<-apply(clustlike,1,max)
for(j in 1:K) {
clustlike[,j]<-exp(clustlike[,j]-tempmax)
}
tempsum<-apply(clustlike,1,sum)
for(j in 1:K) {
clustlike[,j]<-clustlike[,j]/tempsum
}
p.post<-matrix(0,xrow,xcol)
for(j in 1:K) {
for(i in 1:xcol) {
if(patid[j,i] > 0.5) {
p.post[,i]<-p.post[,i]+clustlike[,j]
}
}
}
## return
#calculate back loglikelihood
loglike.old<-loglike.old-sum(log(p))/xrow
loglike.old<-loglike.old*xrow
result<-list(p.post=p.post, motif.prior=p, loglike=loglike.old)
}
generatetype<-function(limfitted)
{
jtype<-list()
df<-limfitted$g1num+limfitted$g2num-2+limfitted$df0
for(j in 1:limfitted$compnum)
{
jtype[[j]]<-list(f0=modt.f0.loglike, f0.param=df[j], f1=modt.f1.loglike, f1.param=c(df[j],limfitted$g1num[j],limfitted$g2num[j],limfitted$v0[j]))
}
jtype
}
cormotiffit <- function(exprs, groupid=NULL, compid=NULL, K=1, tol=1e-3,
max.iter=100, BIC=TRUE, norm.factor.method="TMM",
voom.normalize.method = "none", runtype=c("logCPM","counts","limmafits"), each=3)
{
# first I want to do some typechecking. Input can be either a normalized
# matrix, a count matrix, or a list of limma fits. Dispatch the correct
# limmafit accordingly.
# todo: add some typechecking here
limfitted <- list()
if (runtype=="counts") {DOX_24T_shared_DEGs
limfitted <- limmafit.counts(exprs,groupid,compid, norm.factor.method, voom.normalize.method)
} else if (runtype=="logCPM") {
limfitted <- limmafit.default(exprs,groupid,compid)
} else if (runtype=="limmafits") {
limfitted <- limmafit.list(exprs)
} else {
stop("runtype must be one of 'logCPM', 'counts', or 'limmafits'")
}
jtype<-generatetype(limfitted)
fitresult<-list()
ks <- rep(K, each = each)
fitresult <- bplapply(1:length(ks), function(i, x, type, ks, tol, max.iter) {
cmfit.X(x, type, K = ks[i], tol = tol, max.iter = max.iter)
}, x=limfitted$t, type=jtype, ks=ks, tol=tol, max.iter=max.iter)
best.fitresults <- list()
for (i in 1:length(K)) {
w.k <- which(ks==K[i])
this.bic <- c()
for (j in w.k) this.bic[j] <- -2 * fitresult[[j]]$loglike + (K[i] - 1 + K[i] * limfitted$compnum) * log(dim(limfitted$t)[1])
w.min <- which(this.bic == min(this.bic, na.rm = TRUE))[1]
best.fitresults[[i]] <- fitresult[[w.min]]
}
fitresult <- best.fitresults
bic <- rep(0, length(K))
aic <- rep(0, length(K))
loglike <- rep(0, length(K))
for (i in 1:length(K)) loglike[i] <- fitresult[[i]]$loglike
for (i in 1:length(K)) bic[i] <- -2 * fitresult[[i]]$loglike + (K[i] - 1 + K[i] * limfitted$compnum) * log(dim(limfitted$t)[1])
for (i in 1:length(K)) aic[i] <- -2 * fitresult[[i]]$loglike + 2 * (K[i] - 1 + K[i] * limfitted$compnum)
if(BIC==TRUE) {
bestflag=which(bic==min(bic))
}
else {
bestflag=which(aic==min(aic))
}
result<-list(bestmotif=fitresult[[bestflag]],bic=cbind(K,bic),
aic=cbind(K,aic),loglike=cbind(K,loglike), allmotifs=fitresult)
}
cormotiffitall<-function(exprs,groupid,compid, tol=1e-3, max.iter=100)
{
limfitted<-limmafit(exprs,groupid,compid)
jtype<-generatetype(limfitted)
fitresult<-cmfitall(limfitted$t,type=jtype,tol=1e-3,max.iter=max.iter)
}
cormotiffitsep<-function(exprs,groupid,compid, tol=1e-3, max.iter=100)
{
limfitted<-limmafit(exprs,groupid,compid)
jtype<-generatetype(limfitted)
fitresult<-cmfitsep(limfitted$t,type=jtype,tol=1e-3,max.iter=max.iter)
}
cormotiffitfull<-function(exprs,groupid,compid, tol=1e-3, max.iter=100)
{
limfitted<-limmafit(exprs,groupid,compid)
jtype<-generatetype(limfitted)
fitresult<-cmfitfull(limfitted$t,type=jtype,tol=1e-3,max.iter=max.iter)
}
plotIC<-function(fitted_cormotif)
{
oldpar<-par(mfrow=c(1,2))
plot(fitted_cormotif$bic[,1], fitted_cormotif$bic[,2], type="b",xlab="Motif Number", ylab="BIC", main="BIC")
plot(fitted_cormotif$aic[,1], fitted_cormotif$aic[,2], type="b",xlab="Motif Number", ylab="AIC", main="AIC")
}
plotMotif<-function(fitted_cormotif,title="")
{
layout(matrix(1:2,ncol=2))
u<-1:dim(fitted_cormotif$bestmotif$motif.q)[2]
v<-1:dim(fitted_cormotif$bestmotif$motif.q)[1]
image(u,v,t(fitted_cormotif$bestmotif$motif.q),
col=gray(seq(from=1,to=0,by=-0.1)),xlab="Study",yaxt = "n",
ylab="Corr. Motifs",main=paste(title,"pattern",sep=" "))
axis(2,at=1:length(v))
for(i in 1:(length(u)+1))
{
abline(v=(i-0.5))
}
for(i in 1:(length(v)+1))
{
abline(h=(i-0.5))
}
Ng=10000
if(is.null(fitted_cormotif$bestmotif$p.post)!=TRUE)
Ng=nrow(fitted_cormotif$bestmotif$p.post)
genecount=floor(fitted_cormotif$bestmotif$motif.p*Ng)
NK=nrow(fitted_cormotif$bestmotif$motif.q)
plot(0,0.7,pch=".",xlim=c(0,1.2),ylim=c(0.75,NK+0.25),
frame.plot=FALSE,axes=FALSE,xlab="No. of genes",ylab="", main=paste(title,"frequency",sep=" "))
segments(0,0.7,fitted_cormotif$bestmotif$motif.p[1],0.7)
rect(0,1:NK-0.3,fitted_cormotif$bestmotif$motif.p,1:NK+0.3,
col="dark grey")
mtext(1:NK,at=1:NK,side=2,cex=0.8)
text(fitted_cormotif$bestmotif$motif.p+0.15,1:NK,
labels=floor(fitted_cormotif$bestmotif$motif.p*Ng))
}Set Up Cormotif Data
##Cormotif Log2cpm of Normalized Counts RUVs
#I am going to try this with the log2cpm of the normalized counts from RUVs
set1 <- readRDS("data/Fig3/set1_normalizedcounts_k1.RDS")
lognormcounts_CMF_rep <- as.matrix(set1$normalizedCounts)
lognormcounts_CMF_cpm <- cpm(lognormcounts_CMF_rep + 1, log = TRUE)
#add a pseudocount to ensure any values are not negative or zero
#first want to cut out the replicate samples as not needed for Cormotif
lognormcounts_CMF_cpm <- as.data.frame(lognormcounts_CMF_cpm) %>%
dplyr::select(-(contains("6R"))) %>%
as.matrix()
#14319 genes in 36 cols
write.csv(x = lognormcounts_CMF_cpm, file = "data/Fig3/Cormotif_log2normcounts_RUV_matrix.csv")
lognormcounts_CMF_cpm <- read.csv("data/Fig3/Cormotif_log2normcounts_RUV_matrix.csv")
#14319 genes in 36 columns, set up for plugging into Cormotif
#now I need to set up my groupid and compid accordingly
#put together my group id and comparison id to make the correct comparisons between experimental conditions
#groupid tells which experimental conditions are grouped together
#compid tells which experimental conditions should be compared against one another
##ie DOX24T vs DMSO24T matched control
groupid <- readRDS("data/Fig3/groupid.RDS")
#now I have to make this into a vector (named vector)?
compid <- data.frame(Cond1 = c(1, 2, 3), Cond2 = c(4, 5, 6))Cormotif with RUVs Normalized Counts
#set the seed the same as the previous one to ensure consistency
#fit Cormotif model
# set.seed(19191)
#only set the seed ONCE
# motif.fit_RUV_logNC <- cormotiffit(
# exprs = lognormcounts_CMF_cpm,
# groupid = groupid,
# compid = compid,
# K = 1:8,
# max.iter = 500,
# BIC = TRUE,
# runtype = "logCPM"
# )
# saveRDS(motif.fit_RUV_logNC_cpm, "data/Fig3/motif.fit_RUVnormcounts_log2cpm_250630.RDS")
motif.fit_RUV_logNC_cpm <- readRDS("data/Fig3/motif.fit_RUVnormcounts_log2cpm_250630.RDS")Supplementary Figure 5 - AIC BIC Number of Clusters
#plot the AIC and BIC (we're interested in the Bayesian most of all)
plotIC(motif.fit_RUV_logNC_cpm)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
# bic_aic_file <- file.path(output_folder, "CMF_BIC_AIC_EMP_251022.pdf")
# cairo_pdf(bic_aic_file, width = 6, height = 4)
# plotIC(motif.fit_RUV_logNC_cpm)
# dev.off()
#visual check of the lowest BIC
motif.fit_RUV_logNC_cpm$bic K bic
[1,] 1 167129.9
[2,] 2 166504.4
[3,] 3 166544.8
[4,] 4 166585.1
[5,] 5 166628.6
[6,] 6 166669.3
[7,] 7 166709.8
[8,] 8 166751.7Figure 3A - Cormotif Clusters
I performed gene cluster analysis with the Cormotif package to assess gene expression patterns within these RNAseq data.
#plot the motifs
plotMotif(motif.fit_RUV_logNC_cpm)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#plot the probability legend
myColors <- rev(c("#FFFFFF", "#E6E6E6" ,"#CCCCCC", "#B3B3B3", "#999999", "#808080", "#666666","#4C4C4C", "#333333", "#191919","#000000"))
plot.new()
legend('bottomleft',fill=myColors, legend =rev(c("0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8","0.9", "1")), box.col="white",title = "Probability\nlegend", horiz=FALSE,title.cex=.8)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
Extract posterior probabilities and cluster likelihood
#extract the posterior probability that these genes belong to motifs
gene_prob_all_RUV <- motif.fit_RUV_logNC_cpm$bestmotif$p.post
rownames(gene_prob_all_RUV) <- rownames(lognormcounts_CMF_cpm)
#assign each gene to a motif with max post prob
assigned_motifs_RUV <- apply(gene_prob_all_RUV, 1, which.max)
max_probs_RUV <- apply(gene_prob_all_RUV, 1, max)
#combine these into a dataframe - motif assigned genes (p.post)
motif_assignment_df_RUV <- gene_prob_all_RUV %>%
as.data.frame() %>%
rownames_to_column("Gene") %>%
mutate(
Assigned_Motif = assigned_motifs_RUV[Gene],
Max_Probability = max_probs_RUV[Gene]
)
#extract the cluster likelihood - which DEGs are most likely to be in this cluster
motif_prob_RUV <- motif.fit_RUV_logNC_cpm$bestmotif$clustlike
rownames(motif_prob_RUV) <- rownames(gene_prob_all_RUV)
# write.csv(motif_prob_RUV,"data/Fig3/cormotif_probability_genelist_all_RUV_log2cpm_NormCounts.csv")Integrate P.post and clustlike for final gene sets
#begin with the clustlike cutoffs and then overlay the p.post to check if the genes are present in both
#these filters are the combination of the above analysis to get a gene set that fits in both p.post and clustlike
####Motif 1 - Acute Cluster####
#filter 1: clustlike
clust1_genes_RUV <-
motif_prob_RUV %>%
as.data.frame() %>%
filter(V1>0.8 & V2<0.5) %>%
rownames
length(clust1_genes_RUV)[1] 13600#13600 genes
###filter 2: gene-level posterior pattern
prob_filtered_genes_1_RUV <- rownames(gene_prob_all_RUV[(gene_prob_all_RUV[,1] >0.05 & gene_prob_all_RUV[,1] <0.5 & gene_prob_all_RUV[,2] <0.5 & gene_prob_all_RUV[,3] <0.5),])
### Final intersection of both filters
final_genes_1_RUV <- intersect(clust1_genes_RUV, prob_filtered_genes_1_RUV)
cat("Number of genes passing both filters:", length(final_genes_1_RUV), "\n")Number of genes passing both filters: 7602 #7602 genes pass both filters here
####Motif 2 - Chronic Cluster####
#filter 1: clustlike
clust2_genes_RUV <- motif_prob_RUV %>%
as.data.frame() %>%
filter(V2>0.5 & V1<0.5) %>%
rownames
length(clust2_genes_RUV)[1] 517#517 genes
### Filter 2: Gene-level posterior pattern
prob_filtered_genes_2_RUV <- rownames(gene_prob_all_RUV[(gene_prob_all_RUV[,1] >0.3 & gene_prob_all_RUV[,2] >0.5 & gene_prob_all_RUV[,3] >0.5),])
### Final intersection of both filters
final_genes_2_RUV <- intersect(clust2_genes_RUV, prob_filtered_genes_2_RUV)
cat("Number of genes passing both filters:", length(final_genes_2_RUV), "\n")Number of genes passing both filters: 501 #501 genes pass both filters here
#what is the proportion of my genes that are included?
#p.post and clustlike together
7602+501[1] 8103#8103
(8103/14319)*100[1] 56.58915#56.59% of my genes are represented here out of the 14319 original
#what is the proportion of my genes that are included?
#clustlike only
13600+517[1] 14117#14117
(14117/14319)*100[1] 98.58929#98.6% of my genes are included with clustlike only
#want to find out which genes are not assigned to motifs
final_genes_list_RUV <- union(final_genes_1_RUV, final_genes_2_RUV)
length(final_genes_list_RUV)[1] 8103#8103 genes as found above
initial_genes_list_RUV <- rownames(lognormcounts_CMF_cpm)
length(initial_genes_list_RUV)[1] 14319#14319 genes as usual
unassigned_genes_list_RUV <- setdiff(initial_genes_list_RUV, final_genes_list_RUV)
length(unassigned_genes_list_RUV)[1] 6216#6216 genes not assigned
final_genes_list_clustlike_RUV <- union(clust1_genes_RUV, clust2_genes_RUV)
length(final_genes_list_clustlike_RUV)[1] 14117#14117 genes as above with clustlike only
unassigned_genes_list_RUV_clustlike <- setdiff(initial_genes_list_RUV, final_genes_list_clustlike_RUV)
length(unassigned_genes_list_RUV_clustlike)[1] 202#202 genes not assigned
# saveRDS(unassigned_genes_list_RUV, "data/new/RUV/CMF/unassigned_genes_RUVlog2cpm_NormCounts_Cormotif.RDS")
# saveRDS(unassigned_genes_list_RUV_clustlike, "data/new/RUV/CMF/unassigned_genes_clustlike_RUVslog2cpm_NormCounts_Cormotif.RDS")
#now, ensure that none of these genes are shared amongst categories
vennCor_final_RUV <- list(final_genes_1_RUV, final_genes_2_RUV)
ggVennDiagram(
vennCor_final_RUV,
category.names = c("M1", "M2")
) + ggtitle("Cormotif DEGs clustlike + p.post RUVs log2cpm NC")+
theme(
plot.title = element_text(size = 16, face = "bold"), # Increase title size
text = element_text(size = 16) # Increase text size globally
)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
vennCor_final_RUV_clust <- list(clust1_genes_RUV, clust2_genes_RUV)
ggVennDiagram(
vennCor_final_RUV_clust,
category.names = c("M1", "M2")
) + ggtitle("Cormotif DEGs clustlike RUVs log2cpm NC")+
theme(
plot.title = element_text(size = 16, face = "bold"), # Increase title size
text = element_text(size = 16) # Increase text size globally
)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#no overlapping genes found in these gene sets
clusterdata_dxr_fin_RUV <- data.frame(
Category = c("Motif 1", "Motif 2"),
Value = c(length(final_genes_1_RUV), length(final_genes_2_RUV)
))
clusterdata_dxr_fin_RUV_clust <- data.frame(
Category = c("Motif 1", "Motif 2"),
Value = c(length(clust1_genes_RUV), length(clust2_genes_RUV)
))
piecolors_dxr_fin <- c("Motif 1" = "#83C67C",
"Motif 2" = "#C499C6")
#make this into a barplot
clusterdata_dxr_fin_RUV <- clusterdata_dxr_fin_RUV %>%
mutate(Prop = Value / sum(Value) * 100)
clusterdata_dxr_fin_RUV <- clusterdata_dxr_fin_RUV %>%
mutate(Category = factor(Category, levels = c("Motif 2", "Motif 1"))) %>%
mutate(Prop = Value / sum(Value) * 100)
# stacked bar with no axes
ggplot(clusterdata_dxr_fin_RUV, aes(x = "", y = Value, fill = Category)) +
geom_bar(stat = "identity", width = 0.6) +
geom_text(aes(label = paste0(Value, " (", round(Prop, 1), "%)")),
position = position_stack(vjust = 0.5),
size = 4, color = "white") +
labs(title = "Distr of Gene Clusters Cormotif RUVs clustlike + p.post") +
scale_fill_manual(values = piecolors_dxr_fin) +
theme_void() +
theme(legend.title = element_blank(),
plot.title = element_text(hjust = 0.5))
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#make a piechart of these distributions
clusterdata_dxr_fin_RUV %>% ggplot(aes(x = "", y = Value, fill = Category))+
geom_bar(width = 1, stat = "identity")+
coord_polar("y", start = 0)+
geom_text(aes(label = Value),
position = position_stack(vjust = 0.5),
size = 4, color = "black")+
labs(title = "Distr of Gene Clusters Cormotif RUVs clustlike + p.post", x = NULL, y = NULL)+
theme_void()+
scale_fill_manual(values = piecolors_dxr_fin)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
clusterdata_dxr_fin_RUV_clust %>% ggplot(aes(x = "", y = Value, fill = Category))+
geom_bar(width = 1, stat = "identity")+
coord_polar("y", start = 0)+
geom_text(aes(label = Value),
position = position_stack(vjust = 0.5),
size = 4, color = "black")+
labs(title = "Distr of Gene Clusters Cormotif RUVs clustlike", x = NULL, y = NULL)+
theme_void()+
scale_fill_manual(values = piecolors_dxr_fin)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#now, continue by plotting the logFC of all of these gene sets per motif, as well as look at some random genes for log2cpm to see if the patterns are reflected in the example genes
# saveRDS(final_genes_1_RUV, "data/Fig3/final_genes_1_RUV.RDS")
# saveRDS(final_genes_2_RUV, "data/Fig3/final_genes_2_RUV.RDS")
final_genes_1_RUV <- readRDS("data/Fig3/final_genes_1_RUV.RDS")
final_genes_2_RUV <- readRDS("data/Fig3/final_genes_2_RUV.RDS")
# write.csv(final_genes_1_RUV, "data/Fig3/Recovered_genes_RUV.csv")
# write.csv(final_genes_2_RUV, "data/Fig3/Sustained_genes_RUV.csv")logFC Cormotif over time
####clustlike + p.post logFC of initial set####
##motif 1
length(final_genes_1_RUV)[1] 7602##motif 2
length(final_genes_2_RUV)[1] 501time_col <- c(
"t0" = "#005A4C",
"t24" = "#328477",
"t144" = "#8FB9B1")
#read in my toptables from pairwise analysis
# Toptable_RUV_24T <- read.csv("data/DE/Toptable_RUV_24T_final.csv")
# Toptable_RUV_24R <- read.csv("data/DE/Toptable_RUV_24R_final.csv")
# Toptable_RUV_144R <- read.csv("data/DE/Toptable_RUV_144R_final.csv")
#read in combined toptables
combined_toptables_dxr_RUV <- readRDS("data/DE/combined_toptables_dxr_RUV.RDS")
#Filter the data based on each motif
filt_toptable_1_dxr_fin_RUV <- combined_toptables_dxr_RUV %>%
dplyr::filter(Entrez_ID %in% final_genes_1_RUV) %>%
mutate(absFC = abs(logFC)) %>%
mutate(time = factor(Time, levels = c("t0", "t24", "t144"),
labels = c("t0", "t24", "t144"))) %>%
ggplot(., aes(x = time, y = logFC))+
geom_boxplot(aes(fill = time))+
scale_fill_manual(values = time_col)+
guides(fill = guide_legend(title = "Time"))+
theme_bw()+
xlab(" ")+
ylab("logFC")+
theme_bw()+
ggtitle("LogFC Acute RUVs clustlike + p.post (n=7602)")+
theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
axis.title = element_text(size = 15, colour = "black"),
strip.background = element_rect(fill = "#CAD899"),
axis.text.x = element_text(size = 8, colour = "white", angle = 15),
strip.text.x = element_text(size = 12, colour = "black", face = "bold"))
#motif 2
filt_toptable_2_dxr_fin_RUV <- combined_toptables_dxr_RUV %>%
dplyr::filter(Entrez_ID %in% final_genes_2_RUV) %>%
mutate(absFC = abs(logFC)) %>%
mutate(time = factor(Time, levels = c("t0", "t24", "t144"),
labels = c("t0", "t24", "t144"))) %>%
ggplot(., aes(x = time, y = logFC))+
geom_boxplot(aes(fill = time))+
scale_fill_manual(values = time_col)+
guides(fill = guide_legend(title = "Time"))+
theme_bw()+
xlab(" ")+
ylab("logFC")+
theme_bw()+
ggtitle("LogFC Chronic RUVs clustlike + p.post (n=501)")+
theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
axis.title = element_text(size = 15, colour = "black"),
strip.background = element_rect(fill = "#CAD899"),
axis.text.x = element_text(size = 8, colour = "white", angle = 15),
strip.text.x = element_text(size = 12, colour = "black", face = "bold"))
#plots
filt_toptable_1_dxr_fin_RUV
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
filt_toptable_2_dxr_fin_RUV 
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#now plot the abs logFC for each of these too
filt_toptable_1_abs_fin_RUV <- combined_toptables_dxr_RUV %>%
dplyr::filter(Entrez_ID %in% final_genes_1_RUV) %>%
mutate(absFC = abs(logFC)) %>%
mutate(time = factor(Time, levels = c("t0", "t24", "t144"),
labels = c("t0", "t24", "t144"))) %>%
ggplot(., aes(x = time, y = absFC))+
geom_boxplot(aes(fill = time))+
scale_fill_manual(values = time_col)+
guides(fill = guide_legend(title = "Time"))+
theme_bw()+
xlab(" ")+
ylab("|logFC|")+
theme_bw()+
ggtitle("AbslogFC Acute RUVs clustlike + p.post (n=7602)")+
theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
axis.title = element_text(size = 15, colour = "black"),
strip.background = element_rect(fill = "#CAD899"),
axis.text.x = element_text(size = 8, colour = "white", angle = 15),
strip.text.x = element_text(size = 12, colour = "black", face = "bold"))
#motif 2
filt_toptable_2_abs_fin_RUV <- combined_toptables_dxr_RUV %>%
dplyr::filter(Entrez_ID %in% final_genes_2_RUV) %>%
mutate(absFC = abs(logFC)) %>%
mutate(time = factor(Time, levels = c("t0", "t24", "t144"),
labels = c("t0", "t24", "t144"))) %>%
ggplot(., aes(x = time, y = absFC))+
geom_boxplot(aes(fill = time))+
scale_fill_manual(values = time_col)+
guides(fill = guide_legend(title = "Time"))+
theme_bw()+
xlab(" ")+
ylab("|logFC|")+
theme_bw()+
ggtitle("AbslogFC Chronic RUVs clustlike + p.post (n=501)")+
theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
axis.title = element_text(size = 15, colour = "black"),
strip.background = element_rect(fill = "#CAD899"),
axis.text.x = element_text(size = 8, colour = "white", angle = 15),
strip.text.x = element_text(size = 12, colour = "black", face = "bold"))
#plots
filt_toptable_1_abs_fin_RUV
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
filt_toptable_2_abs_fin_RUV
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
Figure 3B - Top 100 line plot
#load clustlike matrix
motif.fit_RUV_logNC_cpm <- readRDS("data/Fig3/motif.fit_RUVnormcounts_log2cpm_250630.RDS")
clust_mat_100 <- motif.fit_RUV_logNC_cpm$bestmotif$clustlike
#ensure row names match gene IDs
row.names(clust_mat_100) <- row.names(lognormcounts_CMF_cpm)
cmf_logNC_cpm <- clust_mat_100 %>%
as.data.frame() %>%
tibble::rownames_to_column("Entrez_ID") %>%
dplyr::mutate(Entrez_ID = as.character(Entrez_ID))
#Load combined toptables and classify genes
# combined_toptables_dxr_RUV_1 <- dplyr::bind_rows(combined_toptables_dxr_RUV) %>%
# mutate(
# Entrez_ID = as.character(Entrez_ID),
# Time = case_when(
# Time == "24T" ~ "t0",
# Time == "24R" ~ "t24",
# Time == "144R" ~ "t144",
# TRUE ~ NA_character_
# )
# )
# saveRDS(combined_toptables_dxr_RUV_df, "data/DE/combined_toptables_dxr_RUV_df.RDS")
combined_toptables_dxr_RUV_df <- readRDS("data/DE/combined_toptables_dxr_RUV_df.RDS")
#read in full gene universe as I don't want to filter by DEGs only
filcpm_matrix <- readRDS("data/QC/filcpm_final_matrix_newind.RDS")
all_genes <- rownames(filcpm_matrix)
shared <- intersect(rownames(clust_mat_100), all_genes)
clust_mat <- clust_mat_100[shared, , drop = FALSE]
filcpm_mat <- filcpm_matrix[shared, , drop = FALSE]
Sets_cmf_cpmNC <- combined_toptables_dxr_RUV_df %>%
dplyr::mutate(
motif = dplyr::case_when(
Entrez_ID %in% final_genes_1_RUV ~ "Acute",
Entrez_ID %in% final_genes_2_RUV ~ "Chronic",
TRUE ~ "not_assigned"
)
) %>%
dplyr::filter(motif != "not_assigned") %>%
dplyr::left_join(., cmf_logNC_cpm, by = "Entrez_ID") %>%
dplyr::mutate(
Time = factor(Time, levels = c("t0", "t24", "t144")),
absFC = abs(logFC)
)
#get top 100 unique genes per motif by clustlike
gene_scores <- Sets_cmf_cpmNC %>%
dplyr::group_by(Entrez_ID, motif) %>%
dplyr::reframe(
score = ifelse(motif == "Acute", max(V1, na.rm = TRUE), max(V2, na.rm = TRUE)),
.groups = "drop"
)
top100_M1 <- gene_scores %>%
dplyr::filter(motif == "Acute") %>%
dplyr::slice_max(order_by = score, n = 100)
top100_M2 <- gene_scores %>%
dplyr::filter(motif == "Chronic") %>%
dplyr::slice_max(order_by = score, n = 100)
#combine top 100 for plotting
top100_all <- dplyr::bind_rows(top100_M1, top100_M2)
#pull timepoint rows for top 100 genes
plot_df_cpmNC <- Sets_cmf_cpmNC %>%
dplyr::semi_join(top100_all, by = c("Entrez_ID", "motif")) %>%
dplyr::mutate(
absFC = abs(logFC)
)
#calculate median of all genes (not just top 100)
median_allgenes_cpmNC <- Sets_cmf_cpmNC %>%
dplyr::group_by(motif, Time) %>%
dplyr::summarize(
median_logFC = median(logFC, na.rm = TRUE),
median_absFC = median(absFC, na.rm = TRUE),
.groups = "drop"
)
#plotting
motif_cols <- c("Acute" = "#83C67C", "Chronic" = "#C499C6")
#logFC
p_logFC <- ggplot(plot_df_cpmNC, aes(x = Time, y = logFC,
group = Entrez_ID, color = motif)) +
geom_line(alpha = 0.3) +
geom_line(
data = median_allgenes_cpmNC,
aes(x = Time, y = median_logFC,
group = motif, color = motif),
linewidth = 1.2
) +
scale_color_manual(values = motif_cols) +
facet_wrap(~motif, scales = "free_y") +
theme_custom() +
labs(title = "Top 100 motif genes with median - logFC",
x = "Timepoint", y = "logFC") +
theme(
plot.margin = margin(10, 10, 10, 10),
axis.line = element_line(linewidth = 0.8, color = "black"),
axis.ticks.length = unit(0.05, "in"),
legend.position = "right")
# absFC
p_absFC <- ggplot(plot_df_cpmNC, aes(x = Time, y = absFC,
group = Entrez_ID, color = motif)) +
geom_line(alpha = 0.3) +
geom_line(
data = median_allgenes_cpmNC,
aes(x = Time, y = median_absFC,
group = motif, color = motif),
linewidth = 1.2
) +
scale_color_manual(values = motif_cols) +
facet_wrap(~motif, scales = "free_y") +
theme_custom() +
labs(title = "Top 100 motif genes with median trajectory - absFC",
x = "Timepoint", y = "absFC") +
theme(
plot.margin = margin(10, 10, 10, 10),
axis.line = element_line(linewidth = 0.8, color = "black"),
axis.ticks.length = unit(0.05, "in"),
legend.position = "right")
p_logFC
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
p_absFC
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#modify the plots to be on the same thing now that I know they look correct - so no facetingFigure 3B - Top 100 Genes by Motif Cluster
#Figure 3B
plot_motifs100_logFC <- ggplot() +
#top 100 genes per motif
geom_line(data = plot_df_cpmNC,
aes(x = Time, y = logFC,
group = Entrez_ID, color = motif),
alpha = 0.6, size = 1) +
#median lines for M1
geom_line(data = median_allgenes_cpmNC %>%
dplyr::filter(motif == "Acute"),
aes(x = Time, y = median_logFC, group = motif),
color = "#2E8B57", size = 2) +
#median lines for M2
geom_line(data = median_allgenes_cpmNC %>%
dplyr::filter(motif == "Chronic"),
aes(x = Time, y = median_logFC, group = motif),
color = "#7B3F9E", size = 2) +
scale_color_manual(values = motif_cols) +
labs(title = "log2FC Top 100 Genes by Motif",
y = "log2FC", x = "Time", color = "Motif") +
theme_custom() +
theme(
plot.margin = margin(10, 10, 10, 10),
axis.line = element_line(linewidth = 0.8, color = "black"),
axis.ticks.length = unit(0.05, "in"),
legend.position = "right")
plot_motifs100_logFC
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#combine top 100 genes and medians into one plot for absFC
plot_motifs100_abslogFC <- ggplot() +
#top 100 genes per motif
geom_line(data = plot_df_cpmNC,
aes(x = Time, y = absFC,
group = Entrez_ID, color = motif),
alpha = 0.4, size = 0.9) +
#median lines for M1
geom_line(data = median_allgenes_cpmNC %>%
dplyr::filter(motif == "Acute"),
aes(x = Time, y = median_absFC, group = motif),
color = "#2E8B57", size = 2) +
#median lines for M2
geom_line(data = median_allgenes_cpmNC %>%
dplyr::filter(motif == "Chronic"),
aes(x = Time, y = median_absFC, group = motif),
color = "#7B3F9E", size = 2) +
scale_color_manual(values = motif_cols) +
labs(title = "|logFC| Top 100 Genes by Motif",
y = "|logFC|", x = "Time", color = "Motif") +
theme_custom() +
theme(
plot.margin = margin(10, 10, 10, 10),
axis.line = element_line(linewidth = 0.8, color = "black"),
axis.ticks.length = unit(0.05, "in"),
legend.position = "right")
plot_motifs100_abslogFC
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#simple summary table at the end to show the median logFCs
median_summary_cpmNC <- median_allgenes_cpmNC %>%
dplyr::select(motif, Time, median_logFC, median_absFC) %>%
dplyr::arrange(motif, Time)
# View table
print(median_summary_cpmNC)# A tibble: 6 × 4
motif Time median_logFC median_absFC
<chr> <fct> <dbl> <dbl>
1 Acute t0 0.122 0.450
2 Acute t24 0.0248 0.391
3 Acute t144 0.000204 0.137
4 Chronic t0 0.0450 0.939
5 Chronic t24 -1.03 1.56
6 Chronic t144 -0.914 1.22 #save the absFC plot as a pdf and a png for later
# cairo_pdf("data/new/RUV/CMF/abslogFC_lineplot_motifs_clustlike_EMP_250915.pdf", width = 8, height = 6)
# print(plot_motifs100_abslogFC)
# dev.off()
# cairo_pdf("data/new/RUV/CMF/logFC_lineplot_motifs_clustlike_EMP_250915.pdf", width = 8, height = 6)
# print(plot_motifs100_logFC)
# dev.off()
#png file
# ggsave("data/new/RUV/logFC_lineplot_motifs_clustlike_EMP_250915.png", p_logFC, width = 8, height = 6, dpi = 300)
# ggsave("data/new/RUV/abslogFC_lineplot_motifs_clustlike_EMP_250915.png", p_absFC, width = 8, height = 6, dpi = 300)Supplementary Figure 6 - Chronic (n=501) Line Plot
#I want to plot all of the Chronic Cluster M2 genes in a line plot
#No need to slice, include all 501 genes and the median
#load in my combined toptables from limma
combined_toptables_dxr_RUV <- readRDS("data/DE/combined_toptables_dxr_RUV.RDS") %>%
dplyr::select(-X)
#create a toptable with all of the genes marked by motif 1 or motif 2
filt_toptable_motifgenes_RUV <- combined_toptables_dxr_RUV %>%
mutate(motif = case_when(
Entrez_ID %in% final_genes_1_RUV ~ "M1",
Entrez_ID %in% final_genes_2_RUV ~ "M2",
TRUE ~ NA_character_
)) %>%
dplyr::filter(!is.na(motif)) %>%
dplyr::filter(!is.na(SYMBOL)) %>%
mutate(time = factor(Time,
levels = c("t0", "t24", "t144"))) %>%
mutate(absFC = abs(logFC))
plot_M2_allgenes <- filt_toptable_motifgenes_RUV %>%
dplyr::filter(motif == "M2")
#calculate medians for ALL chronic genes across timepoints
medians_motif2_RUV <- plot_M2_allgenes %>%
group_by(time) %>%
summarise(
median_logFC = median(logFC),
median_abslogFC = median(absFC),
.groups = "drop"
)
# Label with median values
labs_logFC_motif2 <- paste0(
"M2\nmedian logFC =\n",
paste0(medians_motif2_RUV$time, "=", round(medians_motif2_RUV$median_logFC, 2), collapse = "\n")
)
#plot all 501 lines for motif 2 genes
plot_motif2_logFC <- ggplot() +
geom_line(data = plot_M2_allgenes,
aes(x = time, y = logFC, group = Entrez_ID),
color = "#C499C6", alpha = 0.4, linewidth = 0.9) +
geom_line(data = medians_motif2_RUV,
aes(x = time, y = median_logFC, group = 1),
color = "#7B3F9E", linewidth = 2) +
labs(title = "log2FC Chronic Genes (n = 501)",
y = "log2FC", x = "Time", color = "Motif") +
theme_custom() +
theme(legend.position = "right")
plot_motif2_logFC
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
# save_plot(plot = plot_motif2_logFC,
# filename = "Motif2_logFC_Supp_EMP",
# folder = output_folder,
# height = 3,
# width = 3)Figure 3C + D - Example genes by cluster
#use the final genes from cross-verifying with clustlike + p.post
#Load in my count matrices
#final_genes_1_RUV
#final_genes_2_RUV
#clust1_genes_RUV
#clust2_genes_RUV
#these are all the genes that are present in each category, make them into dataframes by filtering out the rest of the genes in my main boxplot df
boxplots_cormotif <- readRDS("data/QC/filcpm_matrix_genes.RDS") %>%
as.data.frame()
motif1_genes_fin_RUV <- boxplots_cormotif[boxplots_cormotif$Entrez_ID %in% final_genes_1_RUV,]
dim(motif1_genes_fin_RUV)[1] 7602 44#7602 genes in 44 cols
motif2_genes_fin_RUV <- boxplots_cormotif[boxplots_cormotif$Entrez_ID %in% final_genes_2_RUV,]
dim(motif2_genes_fin_RUV)[1] 501 44#501 genes in 44 cols
#pull out some random genes for each using sample
m1_genes_fin_RUV <- motif1_genes_fin_RUV %>% dplyr::filter(SYMBOL == "ZMYND8")
# motif1_genes_fin_RUV[sample(nrow(motif1_genes_fin_RUV), 3), , drop = FALSE]
#define gene list(s)
#these are the genes pulled out by m1_genes
initial_test_genes1_fin_RUV <- c(m1_genes_fin_RUV$SYMBOL)
#Add more gene symbols as needed or add more categories
#now put in the function I want to use to generate boxplots of genes
process_gene_data_1_fin_RUV <- function(gene) {
gene_data <- m1_genes_fin_RUV %>% filter(SYMBOL == gene)
long_data <- gene_data %>%
pivot_longer(cols = -c(Entrez_ID, SYMBOL), names_to = "Sample", values_to = "log2CPM") %>%
mutate(
Drug = case_when(
grepl("DOX", Sample) ~ "DOX",
grepl("DMSO", Sample) ~ "DMSO",
TRUE ~ NA_character_
),
Timepoint = case_when(
grepl("_24T_", Sample) ~ "24T",
grepl("_24R_", Sample) ~ "24R",
grepl("_144R_", Sample) ~ "144R",
TRUE ~ NA_character_
),
Indv = case_when(
grepl("Ind1$", Sample) ~ "1",
grepl("Ind2$", Sample) ~ "2",
grepl("Ind3$", Sample) ~ "3",
grepl("Ind4$", Sample) ~ "4",
grepl("Ind5$", Sample) ~ "5",
grepl("Ind6$", Sample) ~ "6",
grepl("Ind6REP$", Sample) ~ "6R",
TRUE ~ NA_character_
),
Condition = paste(Drug, Timepoint, sep = "_")
)
long_data$Condition <- factor(
long_data$Condition,
levels = c(
"DOX_24T",
"DMSO_24T",
"DOX_24R",
"DMSO_24R",
"DOX_144R",
"DMSO_144R"
)
)
return(long_data)
}
#generate Boxplots from the above function using our gene list above
for (gene in initial_test_genes1_fin_RUV) {
gene_data <- process_gene_data_1_fin_RUV(gene)
p <- ggplot(gene_data, aes(x = Condition, y = log2CPM, fill = Drug)) +
geom_boxplot(outlier.shape = NA) +
geom_point(aes(color = Indv), size = 2, alpha = 0.5, position = position_jitter(width = -1, height = 0)) +
scale_fill_manual(values = c("DOX" = "#499FBD", "DMSO" = "#BBBBBC")) +
ggtitle(paste("Log2CPM Expression", gene, "Motif 1 RUVs")) +
labs(x = "Treatment", y = "log2CPM") +
theme_bw() +
theme(
plot.title = element_text(size = rel(2), hjust = 0.5),
axis.title = element_text(size = 15, color = "black"),
axis.text.x = element_text(size = 10, color = "black", angle = 90, hjust = 1)
)
print(p)
}
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#####motif 2#####
m2_genes_fin_RUV <- motif2_genes_fin_RUV %>% dplyr::filter(SYMBOL == "CCNB2")
# motif2_genes_fin_RUV[sample(nrow(motif2_genes_fin_RUV), 3), , drop = FALSE]
#define gene list(s)
#these are the genes pulled out by m1_genes
initial_test_genes2_fin_RUV <- c(m2_genes_fin_RUV$SYMBOL)
#Add more gene symbols as needed or add more categories
#now put in the function I want to use to generate boxplots of genes
process_gene_datam2_fin_RUV <- function(gene) {
gene_data <- motif2_genes_fin_RUV %>% filter(SYMBOL == gene)
long_data <- gene_data %>%
pivot_longer(cols = -c(Entrez_ID, SYMBOL), names_to = "Sample", values_to = "log2CPM") %>%
mutate(
Drug = case_when(
grepl("DOX", Sample) ~ "DOX",
grepl("DMSO", Sample) ~ "DMSO",
TRUE ~ NA_character_
),
Timepoint = case_when(
grepl("_24T_", Sample) ~ "24T",
grepl("_24R_", Sample) ~ "24R",
grepl("_144R_", Sample) ~ "144R",
TRUE ~ NA_character_
),
Indv = case_when(
grepl("Ind1$", Sample) ~ "1",
grepl("Ind2$", Sample) ~ "2",
grepl("Ind3$", Sample) ~ "3",
grepl("Ind4$", Sample) ~ "4",
grepl("Ind5$", Sample) ~ "5",
grepl("Ind6$", Sample) ~ "6",
grepl("Ind6REP$", Sample) ~ "6R",
TRUE ~ NA_character_
),
Condition = paste(Drug, Timepoint, sep = "_")
)
long_data$Condition <- factor(
long_data$Condition,
levels = c(
"DOX_24T",
"DMSO_24T",
"DOX_24R",
"DMSO_24R",
"DOX_144R",
"DMSO_144R"
)
)
return(long_data)
}
#this function is saved under process_gene_data so I will save as an R object
#saveRDS(process_gene_data, "data/new/process_gene_data_funct.RDS")
#generate boxplots from the above function using our gene list above
for (gene in initial_test_genes2_fin_RUV) {
gene_data <- process_gene_datam2_fin_RUV(gene)
p <- ggplot(gene_data, aes(x = Condition, y = log2CPM, fill = Drug)) +
geom_boxplot(outlier.shape = NA) +
geom_point(aes(color = Indv), size = 2, alpha = 0.5, position = position_jitter(width = -1, height = 0)) +
scale_fill_manual(values = c("DOX" = "#499FBD", "DMSO" = "#BBBBBC")) +
ggtitle(paste("Log2CPM Expression", gene, "Motif 2 RUVs")) +
labs(x = "Treatment", y = "log2CPM") +
theme_bw() +
theme(
plot.title = element_text(size = rel(2), hjust = 0.5),
axis.title = element_text(size = 15, color = "black"),
axis.text.x = element_text(size = 10, color = "black", angle = 90, hjust = 1)
)
print(p)
}
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
Figure 3E + F - GO KEGG analysis
#now take these final gene sets for each motif - clustlike + p.post consensus genes
#define my background gene set
all_genes [1] "653635" "729737" "102723897" "100132287" "102465432" "100133331"
[7] "79854" "643837" "100130417" "148398" "26155" "339451"
[13] "57801" "9636" "375790" "54991" "51150" "126792"
[19] "388581" "118424" "6339" "116983" "126789" "54973"
[25] "80772" "83756" "1855" "54587" "54998" "81669"
[31] "148413" "55052" "64856" "219293" "83858" "55210"
[37] "339453" "29101" "643988" "142678" "8510" "984"
[43] "728661" "8511" "728642" "9906" "65220" "2782"
[49] "5590" "100506504" "199990" "6497" "79906" "100129534"
[55] "11079" "5192" "55229" "127281" "440556" "63976"
[61] "27237" "1953" "127262" "49856" "57212" "148870"
[67] "388588" "57470" "9731" "1677" "339448" "261734"
[73] "8514" "26038" "6146" "388591" "23463" "387509"
[79] "11332" "83715" "8718" "57449" "79707" "3104"
[85] "9903" "148479" "90326" "55735" "23261" "9341"
[91] "8863" "3604" "11315" "54206" "50651" "473"
[97] "2023" "80045" "9563" "80176" "84275" "199953"
[103] "5293" "22883" "56998" "84328" "64802" "10277"
[109] "23095" "5226" "378708" "1676" "5195" "54897"
[115] "148345" "23435" "10747" "6723" "5394" "2475"
[121] "29914" "26232" "93611" "26270" "10459" "57085"
[127] "4524" "1185" "4878" "4879" "90231" "5351"
[133] "9927" "60672" "55187" "9249" "126755" "10630"
[139] "7799" "23254" "55092" "79180" "842" "23341"
[145] "84301" "6248" "23207" "284723" "54751" "440567"
[151] "729614" "23013" "7709" "27129" "1187" "1188"
[157] "348487" "1969" "128272" "79363" "54455" "26099"
[163] "55707" "114819" "55672" "84809" "11209" "11223"
[169] "9696" "4237" "23400" "6390" "11240" "55920"
[175] "55160" "127707" "8659" "126917" "23352" "23065"
[181] "51154" "100506730" "8574" "54896" "832" "440574"
[187] "644068" "255104" "23252" "55450" "79594" "163933"
[193] "65018" "100861548" "1650" "57576" "400745" "50809"
[199] "8672" "1889" "84224" "249" "5909" "84196"
[205] "401944" "3339" "29092" "998" "54361" "9923"
[211] "2048" "23028" "7798" "100996511" "10236" "80818"
[217] "148898" "6920" "55616" "1870" "3399" "6135"
[223] "6924" "100506963" "57095" "11313" "2582" "3155"
[229] "2517" "55629" "10772" "163702" "57822" "90529"
[235] "57185" "11123" "100506985" "10250" "25932" "25949"
[241] "57035" "23585" "55219" "26119" "57134" "57190"
[247] "56181" "646471" "79000" "164091" "3925" "5051"
[253] "2134" "7780" "84676" "149420" "79927" "51042"
[259] "10256" "64793" "83442" "91544" "79947" "3151"
[265] "6195" "101928728" "8289" "55650" "84243" "54707"
[271] "63906" "10726" "388610" "115572" "6548" "23038"
[277] "84065" "644961" "84958" "9064" "2827" "10163"
[283] "27245" "2537" "199870" "23673" "5511" "6118"
[289] "27293" "55113" "2140" "22826" "93974" "83667"
[295] "54797" "65979" "1104" "8420" "6080" "54952"
[301] "85028" "677838" "6883" "10691" "51441" "2035"
[307] "399474" "6429" "51102" "10076" "9672" "9698"
[313] "79570" "9410" "51538" "2170" "347735" "64129"
[319] "553115" "1307" "576" "90853" "8073" "10657"
[325] "55116" "23633" "200081" "79140" "56063" "55721"
[331] "8668" "339483" "3065" "65108" "100128071" "81629"
[337] "55108" "728116" "653121" "339487" "5928" "81493"
[343] "57648" "8565" "64766" "252995" "113452" "127544"
[349] "204" "113451" "55223" "149076" "1912" "7579"
[355] "114784" "113444" "653160" "100506144" "9204" "79830"
[361] "6421" "9202" "79932" "23154" "5690" "127703"
[367] "63967" "192670" "26523" "192669" "54936" "27095"
[373] "55700" "9967" "79729" "55194" "83931" "84967"
[379] "127700" "64960" "728431" "80149" "64769" "79753"
[385] "7802" "29889" "54955" "55143" "149175" "79693"
[391] "127687" "4520" "3633" "10946" "2275" "51118"
[397] "5453" "64121" "79647" "4725" "23499" "643314"
[403] "353500" "728448" "8761" "26508" "10450" "656"
[409] "54802" "4610" "84879" "10487" "5538" "6018"
[415] "10269" "1298" "64744" "65243" "339559" "64789"
[421] "127396" "9783" "100130557" "4802" "9132" "163732"
[427] "1503" "100507178" "200172" "22955" "100132074" "1907"
[433] "59269" "22887" "284716" "79717" "728621" "10465"
[439] "4904" "64175" "79078" "374969" "114625" "51058"
[445] "6513" "440584" "10969" "149465" "7075" "991"
[451] "64834" "112950" "23334" "5792" "9682" "6487"
[457] "9670" "1802" "533" "8704" "149473" "6536"
[463] "55929" "79033" "55182" "79639" "339541" "11004"
[469] "6202" "266675" "1263" "343521" "149478" "8643"
[475] "8891" "79654" "7389" "57643" "84842" "4595"
[481] "114034" "10420" "126661" "25974" "5052" "10327"
[487] "4678" "149483" "60313" "51249" "3652" "23139"
[493] "8503" "10103" "55624" "541468" "8438" "10489"
[499] "7388" "387338" "2166" "8569" "148932" "64756"
[505] "9813" "6491" "51727" "388630" "54558" "79656"
[511] "11124" "1031" "26994" "22996" "2060" "114883"
[517] "4898" "5865" "51060" "91408" "9372" "200014"
[523] "4998" "84950" "23318" "2882" "65260" "79699"
[529] "55268" "6342" "127435" "1376" "54987" "4116"
[535] "7804" "55706" "54432" "51668" "115353" "9528"
[541] "127428" "606495" "51253" "23648" "619518" "26027"
[547] "338094" "7268" "25973" "1718" "23358" "100507634"
[553] "8613" "5563" "1600" "115209" "114803" "3725"
[559] "55277" "51361" "1573" "4774" "83941" "10207"
[565] "163782" "7398" "85440" "84938" "29929" "23421"
[571] "84455" "5236" "4919" "57685" "55225" "3716"
[577] "205" "9829" "54741" "3953" "5142" "84251"
[583] "79819" "57708" "23169" "26135" "1647" "55970"
[589] "100289178" "9077" "79971" "55635" "57554" "55631"
[595] "9295" "81573" "11147" "1491" "5733" "100132618"
[601] "9406" "406962" "257194" "100526835" "8790" "51086"
[607] "1429" "127253" "204962" "34" "1744" "5876"
[613] "256435" "81849" "10026" "26009" "23032" "374986"
[619] "374987" "91624" "8880" "11080" "54810" "64123"
[625] "23266" "79739" "5567" "80135" "2787" "100505741"
[631] "1486" "117178" "23566" "55283" "126820" "84144"
[637] "148423" "8915" "23576" "3491" "54680" "57489"
[643] "105378828" "51100" "9403" "9653" "8543" "5586"
[649] "2959" "56267" "494115" "2635" "2634" "23507"
[655] "84230" "400761" "55144" "284695" "84146" "164045"
[661] "8317" "7049" "253152" "646817" "23285" "11146"
[667] "79871" "7813" "6125" "388650" "22823" "50999"
[673] "343099" "100131564" "1810" "54874" "8412" "30836"
[679] "2730" "9411" "5825" "2152" "126969" "1266"
[685] "105378862" "729970" "199857" "148534" "100527978" "25950"
[691] "58155" "1806" "51375" "391059" "178" "23443"
[697] "64645" "163786" "54482" "127495" "1629" "100506007"
[703] "8634" "8556" "7412" "2135" "148867" "51611"
[709] "102606465" "101928370" "1901" "1301" "55599" "280"
[715] "55170" "29957" "284611" "113802" "55119" "6814"
[721] "29899" "23155" "22911" "6884" "56900" "57535"
[727] "6301" "1952" "84722" "343263" "6272" "5686"
[733] "284612" "127002" "284613" "57463" "83873" "2773"
[739] "2780" "271" "2948" "2946" "2947" "1435"
[745] "10768" "85369" "257" "388662" "3749" "64783"
[751] "9122" "10542" "3737" "55791" "128338" "10390"
[757] "128344" "5016" "79084" "515" "128346" "100129269"
[763] "5906" "55924" "100506343" "11218" "3752" "55917"
[769] "7482" "54879" "829" "4343" "389" "333926"
[775] "6566" "100506392" "9860" "260425" "10745" "54665"
[781] "10717" "64858" "204851" "56944" "51592" "10286"
[787] "163259" "4893" "7812" "80143" "10100" "4803"
[793] "81839" "845" "55356" "476" "84852" "965"
[799] "3321" "5738" "9398" "8458" "80263" "10905"
[805] "54855" "54834" "10885" "10352" "101929147" "90874"
[811] "26227" "4853" "9554" "728841" "100996724" "101929796"
[817] "101060684" "728855" "653820" "653464" "554282" "100996712"
[823] "284565" "647135" "728833" "103091866" "100288142" "101060254"
[829] "101929780" "653519" "11126" "27246" "10623" "200035"
[835] "10401" "8515" "8799" "9939" "128077" "84265"
[841] "284615" "10628" "148738" "100132406" "388677" "170688"
[847] "149013" "728989" "5565" "171423" "2330" "9557"
[853] "607" "51205" "2702" "51463" "200030" "100132057"
[859] "388685" "25832" "100996763" "440672" "9659" "400818"
[865] "653513" "100996761" "101060226" "653598" "57234" "440689"
[871] "2209" "8370" "105371405" "126961" "8337" "337873"
[877] "723790" "554313" "8349" "51027" "9900" "10262"
[883] "10903" "56957" "11311" "51177" "81611" "23632"
[889] "51107" "79630" "148523" "54460" "9129" "23248"
[895] "80222" "1893" "54507" "4170" "2029" "55204"
[901] "1513" "405" "9869" "29956" "8416" "55793"
[907] "58497" "54964" "56882" "10962" "126626" "10500"
[913] "388695" "79005" "6944" "8394" "5710" "57592"
[919] "5298" "5993" "8991" "5692" "23126" "57530"
[925] "7286" "81609" "65005" "11022" "117145" "6281"
[931] "6282" "6277" "6275" "140576" "6284" "26097"
[937] "23557" "3608" "65123" "11000" "57459" "9909"
[943] "200186" "27173" "148327" "10899" "5872" "6232"
[949] "7170" "25912" "9898" "10456" "89872" "57198"
[955] "3570" "126669" "55585" "103" "3782" "10654"
[961] "57326" "90780" "6464" "1163" "80308" "51043"
[967] "8751" "1945" "1944" "1942" "55974" "54344"
[973] "200185" "80128" "4582" "7059" "4580" "2630"
[979] "2629" "10712" "10067" "1196" "57657" "2224"
[985] "23623" "55870" "645676" "55154" "55249" "7818"
[991] "100129405" "54856" "23208" "6016" "22889" "9181"
[997] "6746" "56893" "28956" "92312" "4000" "64218"
[1003] "9673" "11243" "79957" "23381" "84283" "112770"
[1009] "7203" "4209" "128239" "128240" "54865" "10763"
[1015] "1382" "81875" "51093" "79590" "3068" "5546"
[1021] "375033" "9826" "2117" "55243" "912" "3428"
[1027] "54935" "8407" "57549" "93183" "93185" "477"
[1033] "844" "8682" "50717" "5824" "1314" "474338"
[1039] "23385" "57216" "55600" "50848" "100131187" "7391"
[1045] "257106" "126823" "5202" "4817" "9191" "51506"
[1051] "27005" "5498" "8703" "4720" "84134" "6391"
[1057] "257177" "3310" "11266" "22926" "25903" "9722"
[1063] "400793" "127933" "6675" "4921" "51478" "5999"
[1069] "8490" "83540" "5087" "6258" "4259" "223"
[1075] "54499" "7371" "57645" "117143" "387597" "92235"
[1081] "5451" "8804" "92241" "9019" "25874" "55827"
[1087] "23432" "261726" "375035" "84832" "9095" "101928596"
[1093] "481" "29922" "8548" "57821" "10560" "2153"
[1099] "6403" "92342" "55732" "57147" "22920" "149281"
[1105] "92344" "5396" "2329" "23215" "8674" "51603"
[1111] "26052" "92346" "5279" "51430" "7292" "100506023"
[1117] "9588" "339416" "27252" "91687" "55157" "100506046"
[1123] "60674" "26802" "26774" "26770" "84614" "149041"
[1129] "9910" "27101" "63931" "9674" "64326" "60676"
[1135] "460" "57795" "100302401" "9462" "400798" "55103"
[1141] "9917" "64222" "27" "6646" "163590" "26092"
[1147] "9857" "5768" "200058" "89884" "100527964" "84320"
[1153] "148756" "9213" "57710" "10228" "51278" "2752"
[1159] "6041" "6004" "80896" "1660" "3915" "3918"
[1165] "23057" "284649" "9887" "10092" "23179" "23127"
[1171] "116461" "81563" "80267" "116496" "6045" "81627"
[1177] "54823" "10625" "83872" "7175" "54953" "5743"
[1183] "339479" "101929120" "100616345" "5997" "51377" "6738"
[1189] "51022" "79577" "8707" "343450" "259266" "360023"
[1195] "163486" "388722" "140609" "2494" "23528" "9928"
[1201] "83479" "23271" "23046" "779" "252839" "7139"
[1207] "3898" "7135" "23612" "1465" "89796" "55705"
[1213] "149345" "25802" "10440" "6051" "1999" "127829"
[1219] "29089" "4660" "127833" "10765" "100506696" "5877"
[1225] "59349" "51094" "51706" "92703" "8497" "134"
[1231] "7832" "493" "84719" "9877" "100381270" "6635"
[1237] "9580" "55224" "22874" "84919" "5287" "4194"
[1243] "10446" "23114" "388730" "5929" "25778" "9911"
[1249] "81788" "55220" "5129" "148808" "2005" "85414"
[1255] "64710" "8934" "254428" "284581" "115019" "103021295"
[1261] "338382" "729533" "23380" "9641" "83593" "1939"
[1267] "8444" "9261" "5208" "55432" "1604" "4179"
[1273] "5362" "3914" "50486" "148304" "3664" "27042"
[1279] "255928" "574036" "56256" "55733" "55758" "7188"
[1285] "84791" "7779" "4751" "9926" "25896" "51514"
[1291] "100131205" "5525" "55248" "29937" "467" "25936"
[1297] "128387" "642946" "28982" "79805" "90806" "26750"
[1303] "100505832" "5629" "56950" "5784" "1063" "51133"
[1309] "2104" "55105" "51018" "7042" "127018" "2058"
[1315] "10380" "55699" "25782" "6791" "4139" "79762"
[1321] "54996" "64757" "3142" "11221" "9015" "375056"
[1327] "64853" "148362" "84976" "55061" "824" "7159"
[1333] "105369195" "23219" "8560" "4931" "29097" "80232"
[1339] "149111" "127602" "3930" "55740" "6726" "2052"
[1345] "9725" "10637" "29920" "7044" "163859" "3020"
[1351] "64746" "83881" "286826" "142" "375057" "3707"
[1357] "5664" "56997" "8476" "339500" "100130093" "65094"
[1363] "116841" "7483" "375" "79169" "128308" "2987"
[1369] "200205" "84033" "101927401" "81559" "51127" "92815"
[1375] "149603" "58480" "5867" "126731" "58" "55746"
[1381] "23456" "27097" "9816" "2590" "79605" "22796"
[1387] "183" "84886" "101927604" "79573" "64801" "375061"
[1393] "440730" "128061" "8443" "149371" "83932" "54583"
[1399] "7257" "27184" "57568" "54627" "84284" "80003"
[1405] "84451" "3775" "388753" "6894" "359948" "9804"
[1411] "23029" "51742" "9453" "6905" "148789" "1130"
[1417] "4811" "7107" "56605" "128178" "3964" "55127"
[1423] "88" "4548" "6262" "1131" "56776" "2271"
[1429] "23596" "1122" "9156" "200150" "731275" "9859"
[1435] "10806" "10000" "10472" "159" "51029" "116228"
[1441] "284702" "3192" "101928068" "84288" "55083" "64754"
[1447] "64216" "163882" "51097" "100130097" "25909" "93474"
[1453] "79862" "388759" "7678" "84838" "25893" "343171"
[1459] "80851" "79894" "55657" "267002" "10771" "22982"
[1465] "23185" "23560" "91734" "3422" "22884" "101927824"
[1471] "5214" "10531" "100507034" "1316" "100652988" "1645"
[1477] "10276" "79754" "54906" "2665" "54522" "84893"
[1483] "84991" "5209" "5588" "439949" "57713" "80760"
[1489] "22944" "509" "83860" "10659" "414196" "9712"
[1495] "79746" "254427" "219731" "26019" "55526" "55176"
[1501] "11164" "8872" "57118" "83643" "10133" "55388"
[1507] "5264" "22929" "222389" "8559" "55691" "83641"
[1513] "441549" "51182" "79723" "64421" "414149" "221060"
[1519] "10557" "9397" "221061" "8516" "80013" "9317"
[1525] "389941" "6251" "8029" "1787" "100507347" "7431"
[1531] "338596" "9200" "102723166" "8027" "783" "221078"
[1537] "221079" "84898" "10529" "399726" "387640" "8028"
[1543] "64215" "23412" "648" "100499489" "5305" "22921"
[1549] "256815" "220213" "56243" "57584" "56952" "79896"
[1555] "57512" "23590" "10006" "22852" "10730" "84930"
[1561] "91452" "22931" "143098" "220906" "51322" "25805"
[1567] "102724316" "6840" "57608" "55149" "1326" "645954"
[1573] "220929" "220930" "6935" "94134" "3799" "80314"
[1579] "79741" "3688" "8829" "56288" "8453" "1390"
[1585] "219771" "8325" "57209" "219749" "7581" "7587"
[1591] "399744" "441666" "100129482" "7582" "9790" "5979"
[1597] "55454" "221002" "3185" "8187" "220992" "7580"
[1603] "414208" "6387" "83937" "11067" "220979" "7570"
[1609] "220972" "93550" "253725" "119016" "728407" "100287932"
[1615] "8031" "653268" "728113" "643650" "5540" "9721"
[1621] "83849" "414241" "399761" "2662" "2658" "118738"
[1627] "653145" "642517" "642826" "439965" "102724488" "100996758"
[1633] "414224" "143162" "5599" "58504" "196740" "118461"
[1639] "2074" "55753" "8505" "100652748" "414189" "387680"
[1645] "56624" "259230" "104355295" "653308" "5592" "23283"
[1651] "22943" "11130" "253430" "55847" "7321" "7019"
[1657] "80114" "220965" "220963" "8030" "288" "983"
[1663] "9886" "84159" "219790" "84890" "1959" "29982"
[1669] "221037" "84989" "221035" "29119" "347731" "23411"
[1675] "26091" "84665" "64081" "3189" "55680" "1763"
[1681] "8034" "80312" "55749" "219736" "79009" "9188"
[1687] "26128" "9559" "6832" "80201" "3098" "6865"
[1693] "23555" "219738" "1305" "55506" "84883" "219743"
[1699] "56681" "5464" "55222" "1979" "27143" "140766"
[1705] "8879" "5092" "219699" "728978" "55315" "64115"
[1711] "5660" "9469" "9806" "51008" "119504" "54541"
[1717] "54788" "10367" "90550" "5033" "25961" "11319"
[1723] "317662" "23234" "414245" "51021" "118491" "310"
[1729] "118490" "5532" "159195" "58529" "79933" "729092"
[1735] "729096" "2749" "9632" "170384" "118487" "23053"
[1741] "100507331" "8509" "818" "5328" "7414" "26985"
[1747] "132" "23522" "51207" "142891" "7417" "118881"
[1753] "84858" "100131213" "3778" "9231" "100128292" "11128"
[1759] "6229" "57178" "10105" "219654" "143244" "650623"
[1765] "101060691" "729262" "642361" "80195" "311" "84293"
[1771] "81619" "10718" "27069" "92211" "54462" "2894"
[1777] "23063" "11155" "657" "79812" "6623" "2746"
[1783] "54537" "728118" "728190" "439994" "728130" "9562"
[1789] "9060" "84896" "142913" "100144748" "5728" "57559"
[1795] "100132116" "59" "355" "3988" "3437" "3434"
[1801] "24138" "387700" "53354" "9585" "3363" "10556"
[1807] "27063" "119369" "84333" "143279" "5507" "80351"
[1813] "143282" "9044" "22849" "54708" "3416" "3832"
[1819] "54536" "26509" "55165" "118924" "159371" "266971"
[1825] "51196" "64318" "23232" "3070" "9124" "10580"
[1831] "5832" "26123" "953" "54619" "9849" "7093"
[1837] "56889" "118788" "728658" "102723665" "84458" "26148"
[1843] "84986" "10023" "23401" "23223" "644215" "5223"
[1849] "51013" "84287" "64210" "80019" "118812" "55361"
[1855] "60370" "83742" "118813" "6425" "401647" "55118"
[1861] "27291" "84171" "84795" "3257" "26507" "2805"
[1867] "81894" "57089" "1355" "51076" "23268" "10613"
[1873] "1147" "55280" "282991" "6319" "90271" "25956"
[1879] "4714" "55662" "55719" "57715" "84545" "56652"
[1885] "84445" "81855" "81621" "8945" "27343" "25911"
[1891] "6468" "10360" "10724" "30819" "79591" "79803"
[1897] "8861" "23082" "9221" "8729" "4791" "5662"
[1903] "79176" "79004" "100505761" "79847" "10121" "51684"
[1909] "81603" "403" "118980" "54838" "119032" "54805"
[1915] "22978" "729020" "9118" "84108" "6877" "84833"
[1921] "22984" "51063" "9148" "9644" "79991" "9748"
[1927] "119392" "9446" "119391" "85450" "159686" "22986"
[1933] "114815" "7511" "120" "4601" "10285" "1847"
[1939] "9126" "282996" "282997" "27250" "92482" "8036"
[1945] "150" "57678" "64429" "143187" "6934" "4892"
[1951] "840" "9937" "374354" "153" "55088" "84632"
[1957] "3983" "57700" "142940" "26033" "2674" "259217"
[1963] "57698" "6571" "118987" "22841" "63877" "143384"
[1969] "340719" "8661" "404636" "119559" "10935" "2869"
[1975] "6001" "7073" "9531" "22876" "79892" "11196"
[1981] "196051" "55717" "2263" "11101" "54780" "10579"
[1987] "59338" "5654" "80007" "118672" "64376" "36"
[1993] "9184" "119587" "51363" "4942" "64077" "9679"
[1999] "399818" "23172" "54764" "1488" "26098" "7390"
[2005] "56647" "55760" "92565" "8038" "1793" "642938"
[2011] "5791" "4288" "4255" "387723" "119437" "10539"
[2017] "399827" "55844" "664" "282973" "10570" "282974"
[2023] "80313" "170394" "3632" "54777" "85442" "101"
[2029] "10844" "118472" "282969" "1892" "196743" "92170"
[2035] "503542" "100133161" "51272" "60626" "23410" "5719"
[2041] "80162" "10581" "8519" "10410" "338707" "59307"
[2047] "81490" "6050" "115399" "3265" "256329" "8045"
[2053] "100506211" "57661" "3665" "10522" "283232" "64787"
[2059] "6888" "347862" "171391" "105369190" "51286" "79751"
[2065] "101927423" "55367" "6181" "57104" "283229" "977"
[2071] "5441" "7106" "66005" "161" "54472" "9024"
[2077] "81532" "1850" "338651" "402778" "1509" "6150"
[2083] "283120" "3481" "51214" "29125" "10077" "975"
[2089] "10078" "3784" "10984" "1028" "5002" "7262"
[2095] "4676" "833" "114879" "7748" "650368" "116969"
[2101] "4928" "27315" "391" "6786" "6240" "6737"
[2107] "55128" "117854" "85363" "10346" "84067" "112464"
[2113] "6609" "322" "10612" "23647" "26515" "144132"
[2119] "23378" "3611" "6881" "1200" "8642" "63875"
[2125] "7762" "7761" "143425" "8495" "51700" "8665"
[2131] "7275" "79608" "65975" "9866" "6157" "6764"
[2137] "56672" "56674" "493900" "56675" "57758" "283102"
[2143] "23258" "440026" "10527" "644656" "7702" "7465"
[2149] "23075" "440028" "283104" "81846" "105376544" "133"
[2155] "272" "100463486" "50862" "10335" "9646" "1982"
[2161] "58486" "729013" "374378" "283106" "55031" "27122"
[2167] "9645" "84953" "55742" "7003" "406" "84280"
[2173] "84188" "10418" "22800" "1315" "5682" "5140"
[2179] "120227" "55553" "10944" "144100" "6207" "5286"
[2185] "4925" "374383" "3767" "26297" "113174" "11234"
[2191] "2965" "3939" "7251" "55293" "144108" "144110"
[2197] "54503" "8048" "79733" "89797" "100126784" "100874014"
[2203] "10553" "10196" "203859" "2188" "2620" "258010"
[2209] "159963" "387758" "91057" "55366" "55327" "497258"
[2215] "627" "81930" "196074" "3739" "120534" "744"
[2221] "120526" "196294" "26610" "5954" "7490" "10480"
[2227] "79832" "91614" "55346" "283267" "1479" "10114"
[2233] "25758" "966" "26273" "4005" "4076" "55226"
[2239] "25841" "847" "51074" "8050" "960" "6506"
[2245] "24147" "54765" "143458" "29099" "79899" "7189"
[2251] "5896" "119710" "8539" "55761" "51144" "221120"
[2257] "387763" "84680" "2132" "3732" "90139" "9537"
[2263] "56981" "57586" "8534" "55343" "1408" "9479"
[2269] "9409" "51317" "90993" "8525" "4192" "1132"
[2275] "55626" "283254" "9776" "392" "79797" "9793"
[2281] "4038" "79096" "84364" "29763" "1643" "53"
[2287] "10062" "8567" "4607" "91252" "5702" "10658"
[2293] "114971" "55709" "4722" "23788" "23360" "23279"
[2299] "5795" "85456" "6749" "29015" "8501" "26519"
[2305] "9246" "710" "219539" "10978" "25921" "219541"
[2311] "51075" "280636" "1500" "9404" "80829" "374393"
[2317] "63901" "23220" "5007" "219988" "6809" "54948"
[2323] "79080" "27339" "79073" "54972" "55048" "220001"
[2329] "1642" "26007" "220002" "51524" "51259" "79869"
[2335] "54949" "9066" "113157" "747" "745" "746"
[2341] "2237" "3992" "9415" "3995" "5866" "7439"
[2347] "2495" "3619" "80150" "79026" "1937" "64852"
[2353] "9219" "256364" "6094" "26229" "23193" "80789"
[2359] "102288414" "79081" "751071" "790955" "51035" "26580"
[2365] "221092" "283237" "79842" "5436" "10629" "374395"
[2371] "79064" "10482" "6811" "54663" "23642" "9304"
[2377] "9298" "9303" "6520" "11145" "25923" "10313"
[2383] "65998" "144097" "2011" "283248" "79829" "1351"
[2389] "55611" "28992" "10963" "83706" "83707" "84304"
[2395] "3338" "7423" "2286" "26472" "5331" "56834"
[2401] "572" "2101" "51504" "25824" "283234" "8986"
[2407] "10235" "5837" "7536" "5871" "4221" "55561"
[2413] "10938" "23130" "5526" "402" "29901" "113130"
[2419] "7542" "738" "7108" "741" "2197" "740"
[2425] "84447" "728975" "823" "23649" "10435" "5977"
[2431] "283130" "83786" "283131" "101927789" "378938" "57410"
[2437] "4054" "254100" "10534" "23625" "254102" "4296"
[2443] "399909" "6494" "5970" "10524" "84153" "91056"
[2449] "254122" "1072" "80198" "30008" "9158" "11007"
[2455] "8061" "83638" "10589" "9092" "84285" "8815"
[2461] "89792" "10992" "55690" "64837" "81876" "254263"
[2467] "10897" "256472" "57124" "9610" "25855" "11041"
[2473] "3177" "65003" "246330" "10072" "582" "254359"
[2479] "89" "8722" "55231" "9973" "10432" "5936"
[2485] "83759" "6712" "79703" "9986" "5091" "78999"
[2491] "91683" "29984" "22992" "156" "338692" "54961"
[2497] "57804" "23529" "5883" "5499" "374403" "57571"
[2503] "6199" "5790" "57175" "80194" "9049" "9600"
[2509] "10263" "2950" "4723" "390213" "254552" "347853"
[2515] "645332" "81622" "221" "4728" "10312" "1119"
[2521] "51111" "53838" "4041" "55291" "51083" "9633"
[2527] "1374" "219927" "3508" "219931" "595" "220064"
[2533] "55107" "8772" "8500" "2017" "1717" "55191"
[2539] "55199" "100133315" "55298" "10068" "4926" "100128494"
[2545] "220074" "55004" "25906" "2348" "3636" "81570"
[2551] "5138" "116985" "10809" "89849" "9873" "5029"
[2557] "9828" "84957" "23201" "58473" "5870" "51642"
[2563] "51287" "80227" "7351" "26005" "51400" "283208"
[2569] "283209" "387787" "100287896" "10714" "254225" "143570"
[2575] "9789" "10825" "100507050" "408" "6188" "283212"
[2581] "81544" "871" "4135" "84649" "7405" "7481"
[2587] "5612" "100506127" "56946" "2615" "25987" "55331"
[2593] "726" "5058" "282679" "1207" "51773" "28971"
[2599] "92105" "4718" "79053" "283219" "57558" "9846"
[2605] "79731" "26011" "5547" "220042" "27314" "100506233"
[2611] "51585" "338699" "60492" "1740" "55863" "84233"
[2617] "58487" "54843" "8301" "8726" "51501" "10873"
[2623] "11098" "8322" "65084" "1075" "50507" "10003"
[2629] "26973" "120114" "120103" "56935" "85459" "684959"
[2635] "692063" "654320" "692072" "677805" "677822" "79101"
[2641] "28970" "9440" "24145" "4361" "54851" "2526"
[2647] "143689" "154810" "51503" "55693" "10929" "23052"
[2653] "143686" "100129203" "143684" "9702" "8898" "84441"
[2659] "79780" "8690" "53942" "143872" "83935" "5241"
[2665] "57562" "10413" "330" "329" "114908" "4319"
[2671] "4312" "84259" "79659" "80310" "837" "84437"
[2677] "143879" "60496" "2977" "143884" "91801" "55531"
[2683] "54733" "8065" "38" "4863" "472" "143888"
[2689] "23086" "1662" "85463" "5962" "2230" "57569"
[2695] "143903" "23235" "5519" "79796" "91893" "64776"
[2701] "1410" "3316" "85458" "1737" "120379" "55216"
[2707] "26521" "6392" "83875" "5805" "101928847" "4684"
[2713] "100288346" "54970" "1813" "9183" "57646" "4837"
[2719] "54494" "10179" "25996" "23705" "84811" "8882"
[2725] "335" "23387" "5049" "51092" "100652768" "6876"
[2731] "9159" "257160" "23621" "100379571" "22897" "53826"
[2737] "6330" "6327" "196264" "9354" "10632" "4297"
[2743] "84866" "56912" "372" "23187" "1656" "283149"
[2749] "338657" "6230" "51399" "2542" "10525" "55823"
[2755] "3145" "3014" "1798" "9854" "25988" "64137"
[2761] "79671" "867" "4162" "79102" "9099" "7070"
[2767] "5818" "220323" "219902" "23365" "2900" "219899"
[2773] "7007" "6309" "6653" "399959" "84959" "79864"
[2779] "3312" "57476" "55800" "7753" "4013" "84897"
[2785] "54414" "53340" "79684" "100507283" "219854" "63876"
[2791] "9638" "9538" "3703" "1111" "219844" "83480"
[2797] "50937" "84881" "79607" "6734" "55572" "114609"
[2803] "28960" "6484" "2113" "2313" "3762" "219833"
[2809] "9743" "4798" "56980" "334" "6768" "29068"
[2815] "11095" "170689" "103611081" "399979" "50863" "4978"
[2821] "283174" "22997" "83700" "23310" "112936" "29087"
[2827] "27034" "89944" "27087" "100288778" "6539" "6540"
[2833] "5927" "84318" "283358" "4815" "100049716" "65125"
[2839] "5893" "23085" "81029" "144699" "79602" "196513"
[2845] "775" "2288" "55846" "83714" "2305" "83695"
[2851] "7289" "7004" "10867" "57097" "103752584" "894"
[2857] "57103" "57102" "10635" "8798" "10566" "4704"
[2863] "3742" "3736" "3741" "4908" "928" "7132"
[2869] "4055" "678655" "55080" "6843" "51258" "9918"
[2875] "2597" "25900" "4839" "1108" "57121" "51147"
[2881] "171017" "196500" "50813" "8079" "5763" "27239"
[2887] "10536" "2784" "83461" "8078" "7167" "84727"
[2893] "171220" "10233" "2026" "1822" "113246" "5777"
[2899] "11331" "10436" "10162" "716" "715" "51279"
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[2911] "440078" "8076" "57494" "1911" "4074" "10219"
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[13861] "404281" "6611" "139411" "10549" "23597" "6303"
[13867] "79135" "80311" "1968" "7543" "5165" "9468"
[13873] "5422" "11141" "2710" "257397" "1756" "83604"
[13879] "5638" "7504" "6990" "94122" "8406" "6103"
[13885] "7102" "58526" "54880" "10159" "159013" "9282"
[13891] "8239" "1654" "8573" "4128" "4129" "80258"
[13897] "139341" "7403" "101927574" "55634" "641339" "401588"
[13903] "56548" "84679" "6102" "9767" "9104" "54539"
[13909] "8241" "7317" "8552" "5127" "8237" "7592"
[13915] "203414" "369" "6853" "7076" "2002" "8409"
[13921] "347344" "7569" "57232" "24140" "64840" "10682"
[13927] "4943" "5935" "64743" "6839" "10013" "27344"
[13933] "10245" "10084" "7355" "11040" "55593" "3750"
[13939] "56850" "7030" "90060" "11230" "11152" "27238"
[13945] "79917" "5355" "4007" "28952" "89801" "389856"
[13951] "1184" "139189" "57477" "170685" "55190" "23708"
[13957] "9500" "81557" "728239" "727866" "29057" "54328"
[13963] "64061" "102723508" "8242" "23096" "8243" "3028"
[13969] "10075" "23133" "54954" "65267" "90121" "2245"
[13975] "54552" "10916" "7216" "27301" "90736" "100463488"
[13981] "28986" "158880" "10325" "11279" "29978" "550643"
[13987] "442454" "169981" "474343" "54466" "158586" "7789"
[13993] "139886" "92249" "23229" "139285" "55906" "340554"
[13999] "81887" "4478" "9843" "60401" "367" "4983"
[14005] "286451" "9754" "1947" "64219" "27112" "1896"
[14011] "3476" "51248" "24137" "54857" "105373244" "1741"
[14017] "29934" "4303" "9968" "54413" "9203" "4841"
[14023] "26548" "6872" "8473" "93953" "340527" "441502"
[14029] "340526" "392490" "5303" "54821" "6191" "55869"
[14035] "5255" "4674" "139201" "53344" "7503" "554203"
[14041] "100302692" "6567" "51132" "340533" "22" "139596"
[14047] "646127" "158866" "286495" "51260" "57692" "546"
[14053] "84061" "1349" "538" "441531" "5230" "51616"
[14059] "9452" "254065" "79366" "6451" "27330" "139324"
[14065] "139322" "7552" "1121" "56062" "140886" "4675"
[14071] "286499" "1730" "57526" "64102" "7105" "27286"
[14077] "94121" "1478" "402415" "79979" "59353" "2491"
[14083] "1821" "54457" "1678" "695" "6173" "2717"
[14089] "3188" "100131755" "51309" "54470" "51566" "9823"
[14095] "84460" "11013" "64860" "100528062" "9737" "80823"
[14101] "100287765" "55859" "56271" "90843" "84707" "56849"
[14107] "51186" "27018" "79921" "85012" "9338" "9643"
[14113] "51209" "286527" "767811" "401612" "644353" "286437"
[14119] "139231" "203447" "139221" "55086" "79589" "54885"
[14125] "79710" "55285" "54830" "5631" "1831" "11043"
[14131] "5716" "115201" "1288" "1287" "55916" "2182"
[14137] "105373311" "84187" "9949" "91851" "79868" "154796"
[14143] "57631" "101927352" "5358" "90293" "54521" "139818"
[14149] "3597" "170261" "10857" "203427" "100303728" "292"
[14155] "63932" "7319" "55922" "23157" "6170" "65109"
[14161] "7737" "4694" "79576" "10009" "55026" "23439"
[14167] "3920" "8450" "28985" "29071" "2747" "2892"
[14173] "57187" "331" "10735" "10178" "6594" "4952"
[14179] "8862" "51114" "10813" "63035" "2000" "9131"
[14185] "9363" "55609" "9016" "51634" "55855" "10495"
[14191] "3547" "286467" "51765" "57826" "101928578" "55796"
[14197] "90161" "2239" "2719" "347475" "84295" "3251"
[14203] "84848" "159090" "159091" "56180" "644538" "441518"
[14209] "8933" "26071" "644596" "7626" "203523" "399668"
[14215] "203522" "93380" "10479" "2273" "79649" "27336"
[14221] "9459" "27316" "101928747" "158696" "2258" "100129662"
[14227] "4168" "286410" "23641" "139065" "2332" "2334"
[14233] "3423" "100131434" "91966" "84548" "100506164" "541578"
[14239] "100272228" "10046" "4534" "8776" "83692" "3149"
[14245] "9248" "203547" "79057" "2564" "1069" "50814"
[14251] "7739" "29944" "10838" "55559" "633" "92002"
[14257] "139728" "6535" "10134" "215" "5365" "26576"
[14263] "3421" "6748" "57595" "3897" "393" "8260"
[14269] "5973" "3054" "8269" "3654" "4204" "2316"
[14275] "2010" "6134" "26778" "1774" "6901" "158960"
[14281] "537" "2664" "9130" "55558" "8270" "8266"
[14287] "8273" "60343" "2539" "8517" "139716" "1736"
[14293] "4354" "2157" "8263" "65991" "100272147" "4515"
[14299] "79184" "7411" "116442" "101927830" "474383" "474384"
[14305] "55217" "10251" "6845" "105379416" "6192" "7544"
[14311] "5616" "64595" "8287" "8653" "7404" "22829"
[14317] "246126" "8284" "9086" #pull the gene sets from above for each motif after RUVs correction
final_genes_1_RUV [1] "729737" "102723897" "100132287" "102465432" "100133331" "79854"
[7] "643837" "26155" "339451" "9636" "54991" "51150"
[13] "388581" "118424" "126789" "80772" "83756" "1855"
[19] "54998" "148413" "219293" "83858" "55210" "339453"
[25] "142678" "728642" "65220" "5590" "100506504" "199990"
[31] "6497" "79906" "11079" "55229" "63976" "27237"
[37] "127262" "148870" "388588" "57470" "1677" "261734"
[43] "6146" "23463" "83715" "8718" "79707" "3104"
[49] "9903" "148479" "90326" "23261" "9341" "8863"
[55] "11315" "2023" "80045" "9563" "84275" "199953"
[61] "5293" "22883" "64802" "10277" "23095" "5226"
[67] "10747" "5394" "2475" "29914" "26232" "26270"
[73] "10459" "57085" "4524" "1185" "90231" "9927"
[79] "60672" "9249" "126755" "7799" "55092" "23341"
[85] "84301" "6248" "284723" "729614" "23013" "27129"
[91] "348487" "1969" "54455" "11209" "11223" "9696"
[97] "4237" "6390" "11240" "127707" "23352" "23065"
[103] "51154" "54896" "832" "440574" "644068" "255104"
[109] "23252" "65018" "100861548" "57576" "50809" "1889"
[115] "84196" "401944" "29092" "998" "9923" "2048"
[121] "23028" "7798" "80818" "148898" "6920" "55616"
[127] "3399" "6135" "6924" "100506963" "57095" "11313"
[133] "90529" "57185" "11123" "100506985" "10250" "25932"
[139] "25949" "57035" "23585" "55219" "26119" "57134"
[145] "56181" "646471" "164091" "5051" "2134" "7780"
[151] "84676" "149420" "79927" "51042" "83442" "91544"
[157] "3151" "8289" "84243" "54707" "115572" "23038"
[163] "644961" "9064" "10163" "27245" "23673" "5511"
[169] "6118" "27293" "55113" "2140" "22826" "93974"
[175] "83667" "54797" "65979" "1104" "54952" "85028"
[181] "677838" "51441" "2035" "51102" "10076" "9672"
[187] "9698" "51538" "64129" "553115" "1307" "23633"
[193] "200081" "79140" "8668" "339483" "65108" "55108"
[199] "728116" "339487" "5928" "81493" "57648" "8565"
[205] "127544" "204" "149076" "1912" "114784" "653160"
[211] "5690" "127703" "192670" "192669" "55194" "83931"
[217] "127700" "64960" "728431" "79753" "29889" "149175"
[223] "79693" "127687" "3633" "2275" "64121" "79647"
[229] "4725" "643314" "728448" "8761" "5538" "6018"
[235] "64789" "127396" "9783" "163732" "1503" "100507178"
[241] "200172" "59269" "22887" "728621" "10465" "4904"
[247] "79078" "6513" "440584" "149465" "64834" "5792"
[253] "6487" "1802" "533" "149473" "79639" "339541"
[259] "6202" "79654" "7389" "126661" "5052" "4678"
[265] "60313" "51249" "55624" "2166" "148932" "64756"
[271] "9813" "51727" "388630" "54558" "26994" "2060"
[277] "5865" "51060" "9372" "2882" "79699" "55268"
[283] "6342" "1376" "55706" "51668" "115353" "9528"
[289] "606495" "51253" "23648" "619518" "25973" "23358"
[295] "8613" "5563" "1600" "114803" "83941" "10207"
[301] "85440" "23421" "5236" "4919" "57685" "3716"
[307] "9829" "54741" "3953" "57708" "23169" "55970"
[313] "100289178" "79971" "1491" "257194" "100526835" "1429"
[319] "127253" "204962" "34" "1744" "256435" "81849"
[325] "23032" "374986" "374987" "91624" "11080" "64123"
[331] "23266" "79739" "5567" "100505741" "117178" "23566"
[337] "126820" "84144" "148423" "23576" "57489" "105378828"
[343] "9403" "2959" "56267" "84230" "400761" "55144"
[349] "164045" "646817" "7813" "6125" "388650" "1810"
[355] "54874" "30836" "2730" "9411" "2152" "126969"
[361] "1266" "100527978" "25950" "1806" "178" "64645"
[367] "100506007" "8634" "7412" "148867" "101928370" "1301"
[373] "55599" "284611" "113802" "23155" "22911" "6884"
[379] "6301" "343263" "5686" "284612" "127002" "2780"
[385] "271" "2948" "1435" "10768" "85369" "9122"
[391] "55791" "10390" "128344" "79084" "515" "128346"
[397] "5906" "55924" "11218" "54879" "4343" "389"
[403] "6566" "54665" "204851" "56944" "163259" "7812"
[409] "10100" "81839" "55356" "476" "965" "80263"
[415] "10905" "54855" "54834" "10885" "10352" "101929147"
[421] "90874" "4853" "728841" "100996724" "101929796" "101060684"
[427] "653464" "100996712" "284565" "647135" "100288142" "101060254"
[433] "101929780" "653519" "10623" "200035" "10401" "284615"
[439] "10628" "148738" "100132406" "388677" "149013" "728989"
[445] "5565" "171423" "2330" "607" "51205" "2702"
[451] "51463" "200030" "25832" "100996763" "9659" "400818"
[457] "653513" "100996761" "101060226" "653598" "440689" "2209"
[463] "8370" "105371405" "126961" "8337" "337873" "723790"
[469] "554313" "8349" "10262" "10903" "56957" "11311"
[475] "51177" "81611" "51107" "148523" "54460" "1893"
[481] "1513" "29956" "54964" "10962" "126626" "8394"
[487] "57592" "5298" "5993" "5692" "7286" "81609"
[493] "117145" "6282" "140576" "3608" "65123" "11000"
[499] "57459" "9909" "200186" "27173" "10899" "5872"
[505] "6232" "7170" "89872" "3570" "126669" "55585"
[511] "103" "10654" "90780" "6464" "80308" "1945"
[517] "1942" "80128" "4580" "2630" "2629" "2224"
[523] "55870" "645676" "55249" "7818" "28956" "92312"
[529] "4000" "64218" "9673" "11243" "79957" "84283"
[535] "112770" "4209" "128240" "51093" "5546" "375033"
[541] "9826" "2117" "55243" "57549" "93183" "8682"
[547] "5824" "1314" "474338" "23385" "55600" "100131187"
[553] "7391" "257106" "51506" "8703" "4720" "6391"
[559] "25903" "9722" "127933" "6675" "4921" "51478"
[565] "6258" "223" "54499" "7371" "387597" "25874"
[571] "55827" "375035" "84832" "8548" "10560" "2153"
[577] "6403" "55732" "57147" "5396" "23215" "51603"
[583] "26052" "7292" "100506023" "55157" "100506046" "9910"
[589] "27101" "63931" "9674" "64326" "60676" "100302401"
[595] "55103" "9917" "6646" "163590" "26092" "9857"
[601] "5768" "200058" "100527964" "148756" "9213" "57710"
[607] "10228" "51278" "6041" "80896" "1660" "3918"
[613] "23057" "284649" "9887" "80267" "116496" "81627"
[619] "54823" "83872" "7175" "5743" "101929120" "100616345"
[625] "51377" "6738" "51022" "343450" "360023" "163486"
[631] "388722" "140609" "23528" "23271" "252839" "1465"
[637] "25802" "10440" "6051" "127829" "4660" "127833"
[643] "10765" "51094" "51706" "7832" "493" "55224"
[649] "22874" "84919" "5287" "23114" "388730" "25778"
[655] "81788" "148808" "2005" "85414" "64710" "8934"
[661] "284581" "103021295" "338382" "23380" "83593" "1939"
[667] "8444" "9261" "55432" "5362" "50486" "3664"
[673] "55733" "55758" "7779" "9926" "100131205" "5525"
[679] "55248" "467" "642946" "90806" "100505832" "56950"
[685] "51133" "7042" "2058" "55699" "25782" "4139"
[691] "79762" "54996" "64757" "3142" "375056" "148362"
[697] "84976" "55061" "824" "7159" "23219" "29097"
[703] "80232" "55740" "6726" "2052" "29920" "83881"
[709] "142" "5664" "56997" "8476" "375" "79169"
[715] "2987" "84033" "81559" "51127" "92815" "5867"
[721] "55746" "27097" "9816" "183" "84886" "79573"
[727] "64801" "128061" "8443" "149371" "83932" "54583"
[733] "7257" "27184" "54627" "3775" "6894" "23029"
[739] "51742" "9453" "1130" "7107" "128178" "3964"
[745] "55127" "1131" "56776" "10806" "10000" "159"
[751] "51029" "116228" "284702" "3192" "64754" "51097"
[757] "100130097" "93474" "79862" "388759" "7678" "84838"
[763] "25893" "343171" "80851" "79894" "55657" "22982"
[769] "23185" "23560" "91734" "3422" "22884" "10531"
[775] "54906" "2665" "84893" "84991" "5209" "439949"
[781] "57713" "80760" "22944" "509" "10659" "9712"
[787] "79746" "26019" "55526" "57118" "83643" "10133"
[793] "5264" "22929" "222389" "8559" "83641" "51182"
[799] "64421" "9397" "80013" "8029" "100507347" "783"
[805] "221078" "84898" "10529" "8028" "64215" "648"
[811] "22921" "256815" "220213" "79896" "23590" "10730"
[817] "91452" "143098" "220906" "6840" "645954" "220930"
[823] "6935" "94134" "3799" "8453" "219771" "57209"
[829] "219749" "7587" "399744" "441666" "100129482" "8187"
[835] "220992" "414208" "83937" "220979" "220972" "253725"
[841] "119016" "728407" "100287932" "8031" "653268" "728113"
[847] "643650" "5540" "83849" "414241" "653145" "642517"
[853] "439965" "102724488" "100996758" "414224" "5599" "196740"
[859] "118461" "8505" "414189" "387680" "5592" "23283"
[865] "55847" "7321" "7019" "80114" "8030" "9886"
[871] "29982" "221035" "23411" "64081" "55680" "1763"
[877] "8034" "80312" "219736" "79009" "9188" "9559"
[883] "23555" "55506" "219743" "5464" "55222" "1979"
[889] "140766" "219699" "728978" "55315" "5660" "9469"
[895] "9806" "51008" "119504" "54541" "10367" "90550"
[901] "5033" "23234" "414245" "118491" "118490" "159195"
[907] "58529" "729092" "729096" "170384" "23053" "100507331"
[913] "8509" "818" "5328" "7414" "26985" "132"
[919] "23522" "7417" "118881" "84858" "3778" "9231"
[925] "100128292" "6229" "57178" "10105" "143244" "642361"
[931] "80195" "311" "81619" "10718" "27069" "54462"
[937] "2894" "23063" "657" "79812" "6623" "54537"
[943] "728118" "439994" "728130" "9562" "9060" "84896"
[949] "100132116" "59" "24138" "387700" "119369" "84333"
[955] "143279" "5507" "80351" "22849" "54708" "3416"
[961] "64318" "23232" "9124" "10580" "26123" "953"
[967] "56889" "728658" "102723665" "26148" "23401" "23223"
[973] "84287" "64210" "80019" "55361" "60370" "118813"
[979] "401647" "84171" "84795" "3257" "26507" "2805"
[985] "81894" "10613" "6319" "25956" "4714" "57715"
[991] "56652" "84445" "81855" "8945" "27343" "25911"
[997] "6468" "10724" "30819" "79803" "23082" "9221"
[1003] "8729" "5662" "79176" "79004" "100505761" "79847"
[1009] "10121" "81603" "403" "118980" "119032" "729020"
[1015] "9118" "84108" "6877" "84833" "51063" "9148"
[1021] "9644" "9748" "119391" "85450" "114815" "7511"
[1027] "1847" "9126" "282996" "27250" "92482" "8036"
[1033] "57678" "143187" "55088" "84632" "3983" "57700"
[1039] "142940" "57698" "22841" "143384" "8661" "119559"
[1045] "10935" "7073" "9531" "22876" "79892" "2263"
[1051] "11101" "10579" "59338" "5654" "80007" "64376"
[1057] "9184" "119587" "1488" "26098" "7390" "92565"
[1063] "8038" "1793" "4255" "387723" "119437" "10570"
[1069] "80313" "3632" "54777" "101" "118472" "282969"
[1075] "1892" "196743" "100133161" "51272" "60626" "23410"
[1081] "10410" "81490" "6050" "100506211" "57661" "6888"
[1087] "347862" "171391" "105369190" "55367" "6181" "283229"
[1093] "5441" "66005" "54472" "81532" "338651" "1509"
[1099] "6150" "10078" "10984" "1028" "5002" "7262"
[1105] "4676" "833" "114879" "116969" "27315" "6737"
[1111] "55128" "112464" "6609" "322" "10612" "23378"
[1117] "3611" "6881" "1200" "8642" "8495" "8665"
[1123] "65975" "9866" "6157" "6764" "56672" "56674"
[1129] "493900" "56675" "283102" "23258" "440026" "10527"
[1135] "7702" "7465" "23075" "440028" "81846" "133"
[1141] "100463486" "50862" "9646" "1982" "729013" "374378"
[1147] "55031" "55742" "7003" "84280" "84188" "22800"
[1153] "144100" "6207" "374383" "11234" "2965" "55293"
[1159] "144108" "79733" "89797" "10196" "2188" "2620"
[1165] "258010" "159963" "387758" "55366" "55327" "497258"
[1171] "3739" "26610" "79832" "55346" "283267" "10114"
[1177] "966" "26273" "25841" "847" "8050" "6506"
[1183] "24147" "54765" "79899" "5896" "119710" "55761"
[1189] "387763" "84680" "2132" "3732" "9537" "1408"
[1195] "9479" "9409" "51317" "90993" "8525" "4192"
[1201] "9776" "79797" "9793" "84364" "1643" "53"
[1207] "91252" "5702" "10658" "55709" "23788" "23360"
[1213] "219541" "51075" "9404" "80829" "5007" "79080"
[1219] "79073" "54972" "1642" "220002" "79869" "745"
[1225] "746" "7439" "2495" "79026" "64852" "9219"
[1231] "256364" "6094" "26229" "23193" "80789" "102288414"
[1237] "79081" "751071" "790955" "26580" "283237" "79842"
[1243] "374395" "6811" "54663" "23642" "9303" "6520"
[1249] "11145" "10313" "65998" "2011" "283248" "1351"
[1255] "55611" "10963" "83707" "84304" "3338" "7423"
[1261] "2286" "56834" "572" "25824" "283234" "4221"
[1267] "10938" "23130" "402" "29901" "738" "7108"
[1273] "2197" "740" "823" "10435" "5977" "283130"
[1279] "83786" "378938" "57410" "10534" "23625" "4296"
[1285] "399909" "6494" "84153" "91056" "254122" "1072"
[1291] "9158" "11007" "8061" "10589" "9092" "84285"
[1297] "8815" "89792" "55690" "64837" "256472" "57124"
[1303] "9610" "25855" "3177" "65003" "10072" "582"
[1309] "254359" "8722" "9973" "5936" "79703" "5091"
[1315] "91683" "22992" "156" "338692" "5499" "57571"
[1321] "6199" "57175" "80194" "9600" "10263" "4723"
[1327] "254552" "347853" "221" "10312" "1119" "53838"
[1333] "1374" "595" "220064" "8772" "8500" "2017"
[1339] "1717" "55191" "55199" "100133315" "55298" "10068"
[1345] "100128494" "220074" "25906" "2348" "3636" "5138"
[1351] "10809" "9873" "5029" "84957" "5870" "7351"
[1357] "26005" "51400" "283208" "283209" "387787" "254225"
[1363] "100507050" "6188" "283212" "871" "84649" "5612"
[1369] "100506127" "56946" "25987" "726" "5058" "1207"
[1375] "51773" "28971" "79053" "27314" "51585" "338699"
[1381] "1740" "55863" "58487" "8726" "10873" "11098"
[1387] "8322" "1075" "50507" "10003" "120103" "56935"
[1393] "692072" "677805" "9440" "24145" "54851" "2526"
[1399] "154810" "10929" "23052" "143686" "143684" "79780"
[1405] "8690" "57562" "10413" "330" "80310" "837"
[1411] "4863" "143888" "85463" "2230" "143903" "79796"
[1417] "64776" "1410" "3316" "85458" "1737" "120379"
[1423] "55216" "26521" "83875" "4684" "100288346" "1813"
[1429] "4837" "25996" "8882" "23387" "51092" "9159"
[1435] "23621" "6327" "9354" "10632" "4297" "84866"
[1441] "56912" "23187" "1656" "283149" "338657" "6230"
[1447] "55823" "1798" "25988" "79671" "867" "79102"
[1453] "220323" "23365" "2900" "219899" "6309" "6653"
[1459] "84959" "79864" "3312" "57476" "84897" "79684"
[1465] "63876" "9638" "9538" "3703" "219844" "84881"
[1471] "55572" "114609" "2313" "9743" "56980" "6768"
[1477] "29068" "170689" "50863" "4978" "83700" "112936"
[1483] "27034" "5927" "84318" "283358" "4815" "100049716"
[1489] "65125" "5893" "23085" "81029" "144699" "79602"
[1495] "196513" "775" "2288" "83714" "83695" "7289"
[1501] "7004" "10867" "57097" "103752584" "57103" "8798"
[1507] "10566" "4704" "3742" "4908" "928" "4055"
[1513] "678655" "6843" "51258" "2597" "25900" "4839"
[1519] "1108" "57121" "171017" "8079" "5763" "27239"
[1525] "2784" "8078" "10233" "1822" "11331" "10162"
[1531] "5830" "144195" "6515" "55810" "440078" "8076"
[1537] "57494" "1911" "144571" "642846" "29121" "8531"
[1543] "2120" "100506248" "4040" "54682" "503693" "118426"
[1549] "80824" "387841" "50865" "57613" "83445" "2012"
[1555] "2904" "105369669" "55766" "144608" "51729" "11171"
[1561] "51071" "55885" "728622" "5139" "51026" "80763"
[1567] "2998" "10060" "6660" "586" "11228" "3709"
[1573] "26127" "55711" "51290" "65981" "1663" "58516"
[1579] "160518" "100874249" "196394" "440093" "55196" "10059"
[1585] "51067" "5318" "144245" "55605" "120892" "283464"
[1591] "10138" "51535" "83448" "51135" "5756" "4753"
[1597] "51054" "196527" "196528" "347902" "10411" "55652"
[1603] "51564" "79022" "5213" "121274" "54934" "904"
[1609] "112" "784" "27289" "85478" "51303" "377"
[1615] "8085" "55716" "7846" "84790" "84070" "91010"
[1621] "57701" "100286844" "144233" "84987" "91012" "51474"
[1627] "113251" "466" "4891" "25875" "81566" "6334"
[1633] "160622" "3164" "60673" "3855" "3856" "1975"
[1639] "283335" "23371" "3489" "283337" "84975" "5204"
[1645] "8086" "6667" "54458" "5094" "11016" "517"
[1651] "57658" "25946" "5502" "2647" "967" "10220"
[1657] "84324" "29095" "102724112" "5869" "64375" "6231"
[1663] "5036" "6171" "23344" "140465" "4637" "6601"
[1669] "79035" "1431" "10330" "9924" "6773" "27165"
[1675] "5939" "11176" "10728" "4666" "9880" "4665"
[1681] "6778" "4035" "6472" "246329" "22864" "83729"
[1687] "4141" "10540" "3798" "79837" "115557" "10956"
[1693] "6302" "92979" "25895" "10677" "10106" "9194"
[1699] "338811" "9958" "23041" "57460" "283417" "57522"
[1705] "144577" "283349" "2799" "23592" "253827" "51643"
[1711] "11213" "92797" "23426" "55832" "8445" "56890"
[1717] "57122" "55508" "1368" "11052" "10818" "196446"
[1723] "101928062" "8549" "55266" "23011" "64786" "11010"
[1729] "4673" "5074" "29080" "55117" "400058" "160418"
[1735] "4254" "490" "338758" "4060" "1634" "440107"
[1741] "8411" "7334" "8835" "8738" "57458" "55967"
[1747] "10988" "84101" "4048" "2004" "121441" "5250"
[1753] "121457" "23074" "55681" "400" "79158" "7184"
[1759] "728568" "29915" "50515" "84102" "9891" "255394"
[1765] "55188" "90488" "11153" "9733" "121642" "7374"
[1771] "326625" "84915" "51228" "88455" "488" "51184"
[1777] "29902" "160760" "79600" "160762" "10019" "6311"
[1783] "8315" "80724" "51275" "10961" "10906" "283450"
[1789] "6128" "5781" "84934" "53373" "80024" "196463"
[1795] "9904" "6926" "23389" "79794" "84900" "8739"
[1801] "54997" "23014" "51347" "64426" "26353" "160777"
[1807] "5564" "11021" "10985" "6175" "100506649" "23409"
[1813] "1337" "283459" "8655" "100506668" "84274" "51367"
[1819] "84747" "121665" "80196" "54509" "144406" "6249"
[1825] "65117" "8562" "79720" "23457" "79676" "51329"
[1831] "57605" "10198" "55206" "353116" "10959" "1967"
[1837] "79867" "23545" "80212" "144348" "9612" "57647"
[1843] "114795" "121260" "2054" "5901" "80324" "57634"
[1849] "317781" "57666" "2802" "55743" "7574" "7637"
[1855] "101060200" "284232" "9205" "7750" "2700" "221143"
[1861] "26524" "10284" "650794" "221154" "4285" "5042"
[1867] "9818" "387914" "6049" "10810" "219333" "6144"
[1873] "432369" "255967" "2321" "23281" "6541" "5412"
[1879] "84056" "10208" "23047" "90627" "26960" "8900"
[1885] "4093" "55578" "122011" "10631" "51569" "80209"
[1891] "387921" "10186" "2308" "10166" "1997" "11193"
[1897] "89890" "84078" "9617" "79612" "23078" "11215"
[1903] "55068" "160857" "144811" "101929212" "8848" "641467"
[1909] "55425" "7178" "100190939" "83548" "23091" "8803"
[1915] "55270" "5925" "1102" "22862" "81617" "55213"
[1921] "3839" "57213" "145165" "79621" "220108" "26512"
[1927] "100507398" "115825" "540" "440138" "9724" "4752"
[1933] "100887750" "55901" "51028" "10910" "5100" "27253"
[1939] "81624" "81550" "440145" "22894" "688" "11278"
[1945] "9882" "170622" "7347" "4008" "115207" "26224"
[1951] "23077" "122060" "5457" "64062" "54602" "407975"
[1957] "10257" "10150" "5911" "3843" "8428" "23348"
[1963] "100289373" "337867" "9375" "171425" "5095" "7174"
[1969] "93081" "79070" "2073" "55082" "728215" "55647"
[1975] "55739" "79587" "105376684" "283487" "55608" "8874"
[1981] "10426" "23250" "55795" "8451" "3916" "79774"
[1987] "101928841" "22821" "65110" "283489" "57820" "7011"
[1993] "328" "6035" "55701" "3183" "11198" "57680"
[1999] "84932" "9878" "1603" "63874" "5018" "9056"
[2005] "26020" "54930" "84962" "60686" "5693" "55017"
[2011] "57594" "90673" "105378176" "8106" "116173" "25983"
[2017] "102724814" "55449" "10901" "317749" "4901" "80344"
[2023] "9985" "79711" "10548" "283629" "4738" "51292"
[2029] "26277" "7051" "161424" "56413" "57523" "23351"
[2035] "56948" "23256" "29966" "11154" "25831" "112487"
[2041] "84837" "64067" "112399" "55837" "1073" "6729"
[2047] "283635" "55012" "9692" "5687" "4792" "84312"
[2053] "10484" "122553" "4253" "254170" "145581" "122525"
[2059] "23116" "2287" "57697" "161357" "6235" "6029"
[2065] "4247" "55172" "122773" "23588" "378706" "382"
[2071] "6655" "79944" "8814" "11183" "51062" "60485"
[2077] "51199" "81542" "122786" "145438" "22795" "5706"
[2083] "10979" "10175" "10668" "122809" "55030" "22863"
[2089] "100129075" "3895" "57161" "54916" "10640" "55745"
[2095] "122830" "55860" "5684" "5926" "51339" "64582"
[2101] "112849" "51528" "51635" "5583" "6617" "5529"
[2107] "4522" "7597" "22890" "3306" "26030" "6710"
[2113] "376267" "2342" "4149" "2530" "10243" "64398"
[2119] "51382" "1965" "161145" "51109" "677" "87"
[2125] "8816" "2079" "55334" "9766" "6430" "10001"
[2131] "22990" "26037" "9628" "8110" "53349" "5663"
[2137] "89932" "8650" "79697" "145482" "145483" "51004"
[2143] "80127" "91750" "4053" "9870" "51077" "283571"
[2149] "1743" "83694" "8892" "97" "91754" "10972"
[2155] "2353" "122953" "55640" "11161" "23093" "112752"
[2161] "2103" "100506603" "64207" "85457" "57156" "29954"
[2167] "2954" "283578" "10598" "9517" "2957" "85439"
[2173] "6400" "23768" "55812" "11099" "79882" "161436"
[2179] "1112" "400236" "90141" "55775" "56659" "145567"
[2185] "80017" "9321" "4707" "53981" "79890" "5641"
[2191] "9950" "3705" "64112" "84520" "55148" "55727"
[2197] "57578" "57062" "83982" "57718" "12" "23405"
[2203] "79789" "283596" "51218" "56967" "624" "55102"
[2209] "51527" "10914" "84193" "8812" "317762" "2009"
[2215] "7528" "7453" "79446" "8788" "5527" "1778"
[2221] "3320" "91833" "9895" "23186" "9578" "4140"
[2227] "9529" "79038" "23368" "9556" "400258" "388021"
[2233] "64423" "10572" "122616" "55038" "102723354" "256281"
[2239] "2972" "23241" "100507437" "9112" "283755" "646214"
[2245] "646243" "100132101" "400322" "23191" "114791" "4692"
[2251] "6638" "347746" "8123" "338428" "100033416" "100033431"
[2257] "100033432" "3653" "7337" "2562" "8924" "440248"
[2263] "646278" "56160" "7082" "728498" "22909" "54893"
[2269] "51621" "1139" "26585" "6263" "56851" "440270"
[2275] "57369" "101928174" "723972" "84529" "161742" "10125"
[2281] "11245" "440275" "90427" "56924" "100131244" "388115"
[2287] "85455" "90416" "27079" "2644" "643338" "84936"
[2293] "6692" "57617" "79094" "11261" "51103" "23168"
[2299] "4058" "26015" "30844" "23339" "2595" "64397"
[2305] "8773" "255252" "55142" "57519" "146059" "197131"
[2311] "9836" "161823" "146050" "2923" "80237" "10169"
[2317] "728758" "113201" "51496" "567" "90525" "2628"
[2323] "79029" "7782" "58472" "80031" "50804" "2200"
[2329] "23741" "9728" "2252" "2553" "55056" "100129387"
[2335] "84888" "23431" "23312" "256586" "29767" "29766"
[2341] "5597" "10681" "55930" "4644" "10776" "51187"
[2347] "9236" "145788" "4734" "64864" "374618" "6938"
[2353] "100820829" "102" "4643" "2958" "54832" "114294"
[2359] "771" "9960" "283807" "8925" "79856" "5479"
[2365] "53944" "4947" "348093" "348094" "10081" "10845"
[2371] "54956" "54878" "51495" "10260" "8766" "115752"
[2377] "5604" "6124" "4091" "4088" "64799" "8554"
[2383] "54982" "22801" "10391" "8125" "26035" "54852"
[2389] "6176" "7090" "55323" "79875" "4649" "123228"
[2395] "56965" "3073" "25820" "585" "83440" "101241892"
[2401] "80381" "100287616" "9399" "5371" "64220" "1583"
[2407] "8482" "1198" "1445" "25989" "10066" "57184"
[2413] "9377" "54913" "56905" "79661" "4123" "1464"
[2419] "26263" "145957" "49855" "10099" "79834" "10363"
[2425] "23102" "3419" "3658" "123688" "1512" "5923"
[2431] "23423" "23251" "400410" "283687" "54469" "2184"
[2437] "23184" "390660" "100134869" "440295" "80154" "642402"
[2443] "6218" "100505616" "9455" "83640" "53339" "53346"
[2449] "50810" "440300" "388152" "643707" "374650" "388165"
[2455] "54993" "54581" "4828" "23478" "9640" "642423"
[2461] "101929479" "100133220" "64410" "64963" "3669" "5428"
[2467] "51458" "374654" "8800" "10519" "390637" "51335"
[2473] "64784" "55898" "9899" "400451" "1106" "440311"
[2479] "7026" "91947" "3480" "23336" "7190" "4205"
[2485] "145748" "170691" "55180" "140460" "22856" "6627"
[2491] "123283" "100128108" "105376734" "101927628" "374666" "51728"
[2497] "79622" "4350" "83986" "8312" "58986" "26063"
[2503] "9727" "6650" "9091" "57799" "84326" "89941"
[2509] "9028" "10273" "146330" "65990" "84264" "64788"
[2515] "7329" "8938" "115939" "84572" "64718" "283951"
[2521] "645811" "9894" "9742" "23162" "4832" "197342"
[2527] "90864" "10101" "81889" "51734" "4716" "6187"
[2533] "735301" "2671" "9143" "90850" "4913" "7249"
[2539] "25837" "84231" "1775" "1632" "10921" "57465"
[2545] "527" "5170" "652276" "645644" "83886" "23524"
[2551] "6923" "114984" "84256" "54985" "79228" "100507419"
[2557] "100507458" "7760" "7752" "10127" "7627" "7727"
[2563] "146434" "1773" "10131" "1387" "115" "6345"
[2569] "84662" "57407" "3163" "29965" "124402" "84309"
[2575] "124401" "26048" "29855" "9717" "51172" "196483"
[2581] "79091" "23589" "7874" "29035" "2903" "80063"
[2587] "23274" "8651" "9516" "51061" "26156" "2935"
[2593] "92017" "729993" "51283" "23420" "23042" "123803"
[2599] "353511" "105369154" "54820" "4363" "408050" "102723728"
[2605] "283820" "653190" "6210" "23049" "162073" "51573"
[2611] "57020" "124152" "55623" "123879" "57149" "1428"
[2617] "23117" "100271836" "387254" "51108" "440345" "7385"
[2623] "255762" "730094" "55718" "100131998" "641298" "100132247"
[2629] "57478" "91949" "23062" "124454" "56061" "4706"
[2635] "79728" "84516" "5930" "55114" "342357" "3566"
[2641] "2975" "23247" "23214" "728689" "112869" "6799"
[2647] "728734" "8663" "11273" "7284" "25970" "487"
[2653] "79874" "84901" "83985" "27040" "728888" "552900"
[2659] "440354" "23475" "79447" "9961" "253982" "253980"
[2665] "124446" "9344" "283899" "8448" "226" "83719"
[2671] "654483" "548593" "100526830" "613037" "595101" "26000"
[2677] "197407" "51333" "79077" "22928" "65988" "146540"
[2683] "115509" "78994" "64319" "100862671" "5261" "9274"
[2689] "1489" "9739" "80270" "79759" "339105" "79001"
[2695] "10295" "5652" "2521" "7041" "440359" "124411"
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[7405] "57232" "64840" "10682" "5935" "10013" "27344"
[7411] "10245" "11040" "55593" "3750" "11230" "11152"
[7417] "5355" "4007" "89801" "139189" "57477" "55190"
[7423] "81557" "728239" "727866" "29057" "64061" "3028"
[7429] "10075" "23133" "54954" "90121" "54552" "10916"
[7435] "100463488" "158880" "11279" "550643" "442454" "158586"
[7441] "7789" "23229" "139285" "340554" "81887" "4478"
[7447] "367" "4983" "286451" "1947" "64219" "3476"
[7453] "51248" "54857" "105373244" "4303" "340527" "441502"
[7459] "340526" "392490" "5303" "6191" "5255" "139201"
[7465] "7503" "51132" "22" "158866" "57692" "546"
[7471] "1349" "27330" "139322" "7552" "4675" "286499"
[7477] "1730" "64102" "7105" "27286" "402415" "59353"
[7483] "1821" "54457" "695" "3188" "51566" "9823"
[7489] "100528062" "56271" "27018" "85012" "9338" "51209"
[7495] "286527" "401612" "644353" "203447" "5631" "1831"
[7501] "11043" "1288" "1287" "2182" "105373311" "9949"
[7507] "57631" "54521" "170261" "10857" "100303728" "292"
[7513] "7319" "55922" "23157" "7737" "10009" "3920"
[7519] "29071" "331" "10178" "6594" "9131" "55609"
[7525] "286467" "101928578" "3251" "159091" "56180" "441518"
[7531] "8933" "7626" "93380" "10479" "2273" "27336"
[7537] "158696" "286410" "23641" "2332" "2334" "3423"
[7543] "100131434" "541578" "100272228" "10046" "4534" "8776"
[7549] "83692" "9248" "203547" "79057" "2564" "1069"
[7555] "50814" "10838" "55559" "633" "92002" "10134"
[7561] "215" "3421" "393" "8260" "8269" "3654"
[7567] "2316" "2010" "6134" "1774" "6901" "158960"
[7573] "537" "2664" "55558" "8270" "8266" "60343"
[7579] "8517" "1736" "4354" "8263" "65991" "79184"
[7585] "7411" "101927830" "474383" "474384" "55217" "10251"
[7591] "105379416" "6192" "7544" "5616" "64595" "8287"
[7597] "8653" "7404" "22829" "246126" "8284" "9086" final_genes_2_RUV [1] "64856" "26038" "3604" "79180" "1188" "1870"
[7] "57822" "79000" "3925" "84958" "63967" "55143"
[13] "5453" "26508" "991" "11004" "1263" "6491"
[19] "1031" "4998" "163782" "55635" "55283" "2634"
[25] "8317" "343099" "29899" "57535" "84722" "3737"
[31] "4803" "8458" "653820" "554282" "728833" "23632"
[37] "8991" "6275" "1163" "128239" "8407" "83540"
[43] "339416" "460" "57795" "5997" "259266" "2494"
[49] "9928" "23046" "29089" "55220" "729533" "4751"
[55] "51514" "1063" "10637" "7044" "9156" "55388"
[61] "414149" "8516" "56952" "84930" "2658" "118738"
[67] "11130" "983" "219790" "100144748" "355" "9585"
[73] "3832" "55165" "3070" "55118" "150" "153"
[79] "4288" "399827" "338707" "64787" "283120" "3481"
[85] "6786" "6240" "10346" "7762" "51700" "272"
[91] "81930" "57586" "8534" "29015" "710" "374393"
[97] "220001" "2237" "3619" "80150" "113130" "23649"
[103] "283131" "51083" "9633" "55107" "10714" "220042"
[109] "53826" "3014" "53340" "1111" "2113" "2305"
[115] "10635" "9918" "83461" "397" "441631" "55089"
[121] "10024" "79962" "29127" "25840" "11226" "9700"
[127] "269" "6490" "1017" "8914" "5557" "23306"
[133] "8091" "100128191" "55592" "283431" "121601" "55332"
[139] "55010" "11113" "92558" "9735" "5426" "221150"
[145] "55835" "675" "5983" "79866" "1910" "1880"
[151] "650669" "55320" "5427" "54331" "1033" "11169"
[157] "9787" "5228" "145508" "7443" "1396" "100288637"
[163] "9824" "701" "90417" "57082" "5888" "11339"
[169] "51203" "619189" "79968" "22995" "388121" "9133"
[175] "145773" "9768" "51285" "84465" "55055" "9493"
[181] "10620" "1138" "11173" "57214" "145864" "55215"
[187] "90381" "641" "2242" "9055" "56963" "899"
[193] "124222" "9088" "9074" "9235" "116028" "5347"
[199] "728741" "3835" "112755" "79801" "23594" "23090"
[205] "4501" "55715" "64785" "1006" "23491" "3931"
[211] "51659" "81620" "2175" "359845" "5176" "83903"
[217] "342527" "54478" "9212" "100507131" "6470" "4239"
[223] "10615" "146857" "990" "7153" "29893" "672"
[229] "78995" "146909" "146956" "55771" "83990" "9902"
[235] "3838" "9120" "5608" "3759" "2905" "2232"
[241] "10610" "7083" "332" "84733" "7298" "10403"
[247] "284217" "3613" "5932" "220134" "162681" "23526"
[253] "92840" "10036" "126282" "29128" "147841" "10535"
[259] "55723" "3780" "9518" "7643" "9745" "333"
[265] "284403" "163255" "54922" "27338" "129607" "6241"
[271] "3754" "4613" "6382" "79172" "109" "1058"
[277] "3795" "151056" "822" "30818" "23397" "699"
[283] "150468" "200373" "4175" "3800" "130940" "115677"
[289] "57405" "5163" "83879" "50940" "151246" "26154"
[295] "9427" "55355" "1293" "23178" "343637" "56265"
[301] "83959" "994" "9837" "22974" "1869" "79980"
[307] "81610" "4605" "11065" "55959" "6790" "30811"
[313] "54069" "8208" "54058" "8318" "11200" "129080"
[319] "3976" "4174" "102800317" "79019" "2192" "51512"
[325] "57633" "2177" "6854" "80852" "151648" "56992"
[331] "29122" "993" "10293" "1795" "25886" "55799"
[337] "57650" "7348" "10721" "4171" "7200" "92369"
[343] "4071" "10051" "1894" "8646" "5984" "116832"
[349] "5648" "55214" "80235" "10460" "2261" "5522"
[355] "64151" "3815" "1633" "51191" "3015" "1062"
[361] "8492" "4085" "890" "10733" "84057" "1363"
[367] "3148" "79682" "9319" "375444" "10309" "55789"
[373] "11174" "64105" "891" "64946" "1393" "1719"
[379] "1404" "4001" "4888" "9499" "10112" "995"
[385] "6444" "9232" "3161" "54908" "9945" "100130357"
[391] "221687" "51053" "6941" "6890" "1302" "3833"
[397] "3159" "2289" "1026" "105375039" "266727" "2740"
[403] "860" "221391" "442213" "55166" "4172" "1310"
[409] "7272" "9096" "253714" "202" "387103" "2037"
[415] "113115" "26271" "2852" "4521" "55698" "10457"
[421] "29887" "54443" "7378" "5982" "222183" "27445"
[427] "10926" "4885" "4176" "79690" "43" "375611"
[433] "4897" "1129" "27147" "3792" "2146" "7516"
[439] "54892" "83648" "55790" "1960" "8794" "8797"
[445] "157313" "51435" "157570" "55872" "84296" "4173"
[451] "8836" "254778" "4603" "23213" "5569" "23462"
[457] "25788" "9134" "284" "79075" "29028" "5820"
[463] "9401" "81704" "158326" "347240" "2189" "9833"
[469] "55071" "1164" "401541" "195828" "10592" "54566"
[475] "3371" "26147" "57000" "286204" "29941" "10319"
[481] "84628" "9719" "1757" "89958" "441478" "10742"
[487] "9468" "6839" "60401" "24137" "54821" "9452"
[493] "2491" "11013" "55859" "9363" "51765" "347475"
[499] "644538" "5365" "57595" #Acute Cluster Genes
# acute_genes_matrix <- as.matrix(final_genes_1_RUV)
# colnames(acute_genes_matrix) <- c("Entrez_ID")
# saveRDS(acute_genes_matrix, "data/Fig3/acute_genes_matrix.RDS")
acute_genes_matrix <- readRDS("data/Fig3/acute_genes_matrix.RDS")
length(acute_genes_matrix)[1] 7602#7602 genes in this set for my acute cluster (motif 1)
motif1_mat_GOKEGG_RUV <- gost(query = acute_genes_matrix,
organism = "hsapiens",
ordered_query = FALSE,
measure_underrepresentation = FALSE,
evcodes = TRUE,
user_threshold = 0.05,
significant = TRUE,
custom_bg = all_genes,
correction_method = c("fdr"),
sources = c("GO:BP", "KEGG"))
motif1_GOKEGG_genes_RUV <- gostplot(motif1_mat_GOKEGG_RUV, capped = FALSE, interactive = TRUE)
motif1_GOKEGG_genes_RUVtable_motif1_GOKEGG_genes_RUV <- motif1_mat_GOKEGG_RUV$result %>%
dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))
table_motif1_GOKEGG_genes_RUV %>%
mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>%
kableExtra::kable(.,) %>%
kableExtra::kable_paper("striped", full_width = FALSE) %>%
kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>%
kableExtra::scroll_box(width = "100%", height = "400px")| source | term_id | term_name | intersection_size | term_size | p_value |
|---|---|---|---|---|---|
| GO:BP | GO:0002181 | cytoplasmic translation | 119 | 159 | 4.920e-05 |
| GO:BP | GO:0046907 | intracellular transport | 747 | 1254 | 2.704e-04 |
| GO:BP | GO:0006810 | transport | 1830 | 3261 | 1.952e-03 |
| GO:BP | GO:0051179 | localization | 2247 | 4061 | 1.063e-02 |
| GO:BP | GO:0051234 | establishment of localization | 1960 | 3534 | 2.480e-02 |
| GO:BP | GO:0071705 | nitrogen compound transport | 895 | 1559 | 2.510e-02 |
| GO:BP | GO:0009057 | macromolecule catabolic process | 712 | 1228 | 3.449e-02 |
| GO:BP | GO:0019538 | protein metabolic process | 2065 | 3740 | 3.490e-02 |
| GO:BP | GO:0015986 | proton motive force-driven ATP synthesis | 51 | 66 | 3.490e-02 |
| GO:BP | GO:0030163 | protein catabolic process | 531 | 904 | 4.699e-02 |
| GO:BP | GO:0006754 | ATP biosynthetic process | 62 | 84 | 4.699e-02 |
| GO:BP | GO:0033365 | protein localization to organelle | 531 | 905 | 4.699e-02 |
| KEGG | KEGG:05171 | Coronavirus disease - COVID-19 | 122 | 162 | 4.675e-07 |
| KEGG | KEGG:03010 | Ribosome | 94 | 128 | 1.346e-04 |
| KEGG | KEGG:05012 | Parkinson disease | 151 | 227 | 1.081e-03 |
| KEGG | KEGG:04142 | Lysosome | 84 | 118 | 1.806e-03 |
| KEGG | KEGG:00190 | Oxidative phosphorylation | 77 | 107 | 1.806e-03 |
| KEGG | KEGG:05016 | Huntington disease | 166 | 258 | 3.392e-03 |
| KEGG | KEGG:05010 | Alzheimer disease | 199 | 317 | 4.988e-03 |
| KEGG | KEGG:04144 | Endocytosis | 147 | 228 | 5.699e-03 |
| KEGG | KEGG:05022 | Pathways of neurodegeneration - multiple diseases | 237 | 391 | 1.855e-02 |
| KEGG | KEGG:05415 | Diabetic cardiomyopathy | 110 | 169 | 1.855e-02 |
| KEGG | KEGG:05132 | Salmonella infection | 135 | 213 | 2.234e-02 |
| KEGG | KEGG:05208 | Chemical carcinogenesis - reactive oxygen species | 116 | 181 | 2.599e-02 |
| KEGG | KEGG:05014 | Amyotrophic lateral sclerosis | 186 | 306 | 4.495e-02 |
#GO:BP
table_motif1_genes_GOBP_RUV <- table_motif1_GOKEGG_genes_RUV %>%
dplyr::filter(source=="GO:BP") %>%
dplyr::select(p_value, term_name, intersection_size) %>%
dplyr::slice_min(., n=20, order_by=p_value) %>%
mutate(log_val = -log10(p_value))
table_motif1_genes_GOBP_RUV %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value))) +
geom_point() +
ggtitle("M1 Enriched GO:BP Terms RUVs")+
xlab(expression("-log"[10]~"p-value"))+
guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
ylab("GO:BP term")+
scale_y_discrete(labels = scales::label_wrap(30))+
theme_custom()
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#KEGG
table_motif1_genes_KEGG_RUV <- table_motif1_GOKEGG_genes_RUV %>%
dplyr::filter(source=="KEGG") %>%
dplyr::select(p_value, term_name, intersection_size) %>%
dplyr::slice_min(., n=20, order_by=p_value) %>%
mutate(log_val = -log10(p_value))
table_motif1_genes_KEGG_RUV %>%
ggplot(aes(x = log_val, y = reorder(term_name, p_value))) +
geom_point(aes(size = intersection_size)) +
ggtitle("Recovered Enriched Biological Pathways") +
xlab(expression("-log"[10]~"p-value")) +
ylab("KEGG Term") +
scale_y_discrete(labels = scales::label_wrap(30)) +
theme_custom()
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#Chronic Cluster Genes
# chronic_genes_matrix <- as.matrix(final_genes_2_RUV)
# colnames(chronic_genes_matrix) <- c("Entrez_ID")
# saveRDS(chronic_genes_matrix, "data/Fig3/chronic_genes_matrix.RDS")
chronic_genes_matrix <- readRDS("data/Fig3/chronic_genes_matrix.RDS")
length(chronic_genes_matrix)[1] 501#501 genes in the chronic cluster (motif2)
motif2_mat_GOKEGG_RUV <- gost(query = chronic_genes_matrix,
organism = "hsapiens",
ordered_query = FALSE,
measure_underrepresentation = FALSE,
evcodes = TRUE,
user_threshold = 0.05,
custom_bg = all_genes,
correction_method = c("fdr"),
sources = c("GO:BP", "KEGG"))
motif2_GOKEGG_genes_RUV <- gostplot(motif2_mat_GOKEGG_RUV, capped = FALSE, interactive = TRUE)
motif2_GOKEGG_genes_RUVtable_motif2_GOKEGG_genes_RUV <- motif2_mat_GOKEGG_RUV$result %>%
dplyr::select(c(source, term_id, term_name, intersection_size, term_size, p_value))
table_motif2_GOKEGG_genes_RUV %>%
mutate_at(.vars = 6, .funs = scales::label_scientific(digits=4)) %>%
kableExtra::kable(.,) %>%
kableExtra::kable_paper("striped", full_width = FALSE) %>%
kableExtra::kable_styling(full_width = FALSE, position = "left", bootstrap_options = c("striped", "hover")) %>%
kableExtra::scroll_box(width = "100%", height = "400px")| source | term_id | term_name | intersection_size | term_size | p_value |
|---|---|---|---|---|---|
| GO:BP | GO:0022402 | cell cycle process | 175 | 1094 | 3.270e-67 |
| GO:BP | GO:1903047 | mitotic cell cycle process | 134 | 687 | 4.039e-60 |
| GO:BP | GO:0007049 | cell cycle | 185 | 1392 | 7.748e-59 |
| GO:BP | GO:0000278 | mitotic cell cycle | 141 | 809 | 1.929e-57 |
| GO:BP | GO:0000280 | nuclear division | 95 | 358 | 6.878e-54 |
| GO:BP | GO:0007059 | chromosome segregation | 97 | 380 | 1.677e-53 |
| GO:BP | GO:0048285 | organelle fission | 96 | 403 | 5.185e-50 |
| GO:BP | GO:0098813 | nuclear chromosome segregation | 80 | 278 | 6.767e-48 |
| GO:BP | GO:0051301 | cell division | 109 | 575 | 6.248e-47 |
| GO:BP | GO:0010564 | regulation of cell cycle process | 111 | 626 | 6.781e-45 |
| GO:BP | GO:0140014 | mitotic nuclear division | 73 | 258 | 5.573e-43 |
| GO:BP | GO:0051276 | chromosome organization | 95 | 485 | 1.029e-41 |
| GO:BP | GO:0000070 | mitotic sister chromatid segregation | 62 | 185 | 3.879e-41 |
| GO:BP | GO:0000819 | sister chromatid segregation | 66 | 223 | 4.486e-40 |
| GO:BP | GO:0051726 | regulation of cell cycle | 126 | 928 | 8.991e-39 |
| GO:BP | GO:0044770 | cell cycle phase transition | 89 | 483 | 1.008e-36 |
| GO:BP | GO:0044772 | mitotic cell cycle phase transition | 78 | 397 | 7.054e-34 |
| GO:BP | GO:0006260 | DNA replication | 63 | 259 | 1.188e-32 |
| GO:BP | GO:1901987 | regulation of cell cycle phase transition | 75 | 386 | 3.574e-32 |
| GO:BP | GO:0007346 | regulation of mitotic cell cycle | 78 | 442 | 1.544e-30 |
| GO:BP | GO:1905818 | regulation of chromosome separation | 35 | 74 | 7.224e-29 |
| GO:BP | GO:0051321 | meiotic cell cycle | 52 | 195 | 7.919e-29 |
| GO:BP | GO:0051983 | regulation of chromosome segregation | 43 | 125 | 9.994e-29 |
| GO:BP | GO:0007088 | regulation of mitotic nuclear division | 40 | 106 | 1.687e-28 |
| GO:BP | GO:0000075 | cell cycle checkpoint signaling | 50 | 181 | 1.687e-28 |
| GO:BP | GO:0051783 | regulation of nuclear division | 42 | 121 | 2.895e-28 |
| GO:BP | GO:0010948 | negative regulation of cell cycle process | 59 | 266 | 2.895e-28 |
| GO:BP | GO:0006261 | DNA-templated DNA replication | 46 | 151 | 3.056e-28 |
| GO:BP | GO:1903046 | meiotic cell cycle process | 45 | 144 | 3.744e-28 |
| GO:BP | GO:1901990 | regulation of mitotic cell cycle phase transition | 62 | 303 | 9.923e-28 |
| GO:BP | GO:0051304 | chromosome separation | 35 | 80 | 1.480e-27 |
| GO:BP | GO:1901988 | negative regulation of cell cycle phase transition | 54 | 230 | 4.020e-27 |
| GO:BP | GO:0090068 | positive regulation of cell cycle process | 52 | 216 | 1.212e-26 |
| GO:BP | GO:0051310 | metaphase chromosome alignment | 37 | 98 | 2.073e-26 |
| GO:BP | GO:0140013 | meiotic nuclear division | 41 | 128 | 4.248e-26 |
| GO:BP | GO:0045786 | negative regulation of cell cycle | 63 | 335 | 4.269e-26 |
| GO:BP | GO:0007093 | mitotic cell cycle checkpoint signaling | 41 | 134 | 3.107e-25 |
| GO:BP | GO:0051303 | establishment of chromosome localization | 37 | 105 | 3.457e-25 |
| GO:BP | GO:0050000 | chromosome localization | 38 | 113 | 4.841e-25 |
| GO:BP | GO:1902850 | microtubule cytoskeleton organization involved in mitosis | 43 | 158 | 3.116e-24 |
| GO:BP | GO:0010965 | regulation of mitotic sister chromatid separation | 29 | 61 | 4.438e-24 |
| GO:BP | GO:0045787 | positive regulation of cell cycle | 55 | 278 | 8.660e-24 |
| GO:BP | GO:0051306 | mitotic sister chromatid separation | 29 | 64 | 2.438e-23 |
| GO:BP | GO:1901991 | negative regulation of mitotic cell cycle phase transition | 42 | 160 | 5.296e-23 |
| GO:BP | GO:0051784 | negative regulation of nuclear division | 28 | 60 | 5.668e-23 |
| GO:BP | GO:0006259 | DNA metabolic process | 98 | 874 | 5.874e-23 |
| GO:BP | GO:0033048 | negative regulation of mitotic sister chromatid segregation | 26 | 50 | 6.743e-23 |
| GO:BP | GO:2000816 | negative regulation of mitotic sister chromatid separation | 26 | 50 | 6.743e-23 |
| GO:BP | GO:0045841 | negative regulation of mitotic metaphase/anaphase transition | 26 | 50 | 6.743e-23 |
| GO:BP | GO:0033046 | negative regulation of sister chromatid segregation | 26 | 50 | 6.743e-23 |
| GO:BP | GO:0033047 | regulation of mitotic sister chromatid segregation | 27 | 56 | 1.158e-22 |
| GO:BP | GO:1905819 | negative regulation of chromosome separation | 26 | 51 | 1.232e-22 |
| GO:BP | GO:1902100 | negative regulation of metaphase/anaphase transition of cell cycle | 26 | 51 | 1.232e-22 |
| GO:BP | GO:0051985 | negative regulation of chromosome segregation | 26 | 51 | 1.232e-22 |
| GO:BP | GO:0007051 | spindle organization | 45 | 193 | 1.790e-22 |
| GO:BP | GO:0045839 | negative regulation of mitotic nuclear division | 27 | 58 | 3.507e-22 |
| GO:BP | GO:0033045 | regulation of sister chromatid segregation | 34 | 103 | 3.670e-22 |
| GO:BP | GO:0071174 | mitotic spindle checkpoint signaling | 25 | 48 | 4.338e-22 |
| GO:BP | GO:0007094 | mitotic spindle assembly checkpoint signaling | 25 | 48 | 4.338e-22 |
| GO:BP | GO:0071173 | spindle assembly checkpoint signaling | 25 | 48 | 4.338e-22 |
| GO:BP | GO:0045930 | negative regulation of mitotic cell cycle | 46 | 208 | 5.348e-22 |
| GO:BP | GO:0031577 | spindle checkpoint signaling | 25 | 49 | 8.289e-22 |
| GO:BP | GO:0007091 | metaphase/anaphase transition of mitotic cell cycle | 32 | 95 | 3.613e-21 |
| GO:BP | GO:0044784 | metaphase/anaphase transition of cell cycle | 32 | 96 | 5.161e-21 |
| GO:BP | GO:0008608 | attachment of spindle microtubules to kinetochore | 25 | 52 | 5.405e-21 |
| GO:BP | GO:0007052 | mitotic spindle organization | 36 | 128 | 7.080e-21 |
| GO:BP | GO:0030071 | regulation of mitotic metaphase/anaphase transition | 31 | 91 | 1.110e-20 |
| GO:BP | GO:1902099 | regulation of metaphase/anaphase transition of cell cycle | 31 | 92 | 1.595e-20 |
| GO:BP | GO:0061982 | meiosis I cell cycle process | 29 | 84 | 1.660e-19 |
| GO:BP | GO:0006281 | DNA repair | 69 | 568 | 1.228e-17 |
| GO:BP | GO:0033044 | regulation of chromosome organization | 43 | 232 | 1.985e-17 |
| GO:BP | GO:0045132 | meiotic chromosome segregation | 24 | 62 | 2.008e-17 |
| GO:BP | GO:0000226 | microtubule cytoskeleton organization | 68 | 562 | 2.758e-17 |
| GO:BP | GO:0006270 | DNA replication initiation | 19 | 35 | 3.549e-17 |
| GO:BP | GO:0044839 | cell cycle G2/M phase transition | 34 | 146 | 6.888e-17 |
| GO:BP | GO:0000086 | G2/M transition of mitotic cell cycle | 32 | 131 | 1.577e-16 |
| GO:BP | GO:0006974 | DNA damage response | 83 | 826 | 2.650e-16 |
| GO:BP | GO:2001251 | negative regulation of chromosome organization | 27 | 93 | 5.828e-16 |
| GO:BP | GO:0007127 | meiosis I | 25 | 79 | 9.453e-16 |
| GO:BP | GO:0007017 | microtubule-based process | 79 | 791 | 2.648e-15 |
| GO:BP | GO:0010389 | regulation of G2/M transition of mitotic cell cycle | 26 | 98 | 2.637e-14 |
| GO:BP | GO:1905820 | positive regulation of chromosome separation | 16 | 30 | 2.950e-14 |
| GO:BP | GO:0051225 | spindle assembly | 29 | 126 | 3.217e-14 |
| GO:BP | GO:0007080 | mitotic metaphase chromosome alignment | 21 | 60 | 3.393e-14 |
| GO:BP | GO:0019953 | sexual reproduction | 69 | 684 | 1.911e-13 |
| GO:BP | GO:0022414 | reproductive process | 86 | 988 | 3.410e-13 |
| GO:BP | GO:1902749 | regulation of cell cycle G2/M phase transition | 26 | 109 | 4.043e-13 |
| GO:BP | GO:0051984 | positive regulation of chromosome segregation | 15 | 29 | 4.217e-13 |
| GO:BP | GO:0006310 | DNA recombination | 41 | 283 | 8.707e-13 |
| GO:BP | GO:0000727 | double-strand break repair via break-induced replication | 10 | 11 | 1.693e-12 |
| GO:BP | GO:0044771 | meiotic cell cycle phase transition | 10 | 11 | 1.693e-12 |
| GO:BP | GO:0044786 | cell cycle DNA replication | 17 | 43 | 1.773e-12 |
| GO:BP | GO:0051988 | regulation of attachment of spindle microtubules to kinetochore | 13 | 22 | 2.483e-12 |
| GO:BP | GO:0051656 | establishment of organelle localization | 50 | 424 | 4.158e-12 |
| GO:BP | GO:0033260 | nuclear DNA replication | 16 | 39 | 4.898e-12 |
| GO:BP | GO:0000725 | recombinational repair | 31 | 175 | 5.896e-12 |
| GO:BP | GO:0006302 | double-strand break repair | 40 | 291 | 9.922e-12 |
| GO:BP | GO:0034508 | centromere complex assembly | 14 | 29 | 1.052e-11 |
| GO:BP | GO:0000724 | double-strand break repair via homologous recombination | 30 | 170 | 1.590e-11 |
| GO:BP | GO:0090329 | regulation of DNA-templated DNA replication | 15 | 36 | 2.113e-11 |
| GO:BP | GO:1901989 | positive regulation of cell cycle phase transition | 23 | 101 | 3.652e-11 |
| GO:BP | GO:0051383 | kinetochore organization | 12 | 21 | 3.826e-11 |
| GO:BP | GO:0006996 | organelle organization | 175 | 2998 | 4.266e-11 |
| GO:BP | GO:1901992 | positive regulation of mitotic cell cycle phase transition | 21 | 87 | 1.057e-10 |
| GO:BP | GO:0051640 | organelle localization | 55 | 543 | 1.089e-10 |
| GO:BP | GO:0030174 | regulation of DNA-templated DNA replication initiation | 10 | 14 | 1.200e-10 |
| GO:BP | GO:0006275 | regulation of DNA replication | 23 | 107 | 1.255e-10 |
| GO:BP | GO:0031570 | DNA integrity checkpoint signaling | 24 | 121 | 2.613e-10 |
| GO:BP | GO:0051315 | attachment of mitotic spindle microtubules to kinetochore | 12 | 25 | 5.556e-10 |
| GO:BP | GO:0045931 | positive regulation of mitotic cell cycle | 23 | 115 | 5.938e-10 |
| GO:BP | GO:0007143 | female meiotic nuclear division | 13 | 31 | 6.415e-10 |
| GO:BP | GO:0051231 | spindle elongation | 9 | 12 | 7.328e-10 |
| GO:BP | GO:0051256 | mitotic spindle midzone assembly | 8 | 9 | 8.982e-10 |
| GO:BP | GO:0090307 | mitotic spindle assembly | 18 | 71 | 1.489e-09 |
| GO:BP | GO:1901976 | regulation of cell cycle checkpoint | 15 | 47 | 1.723e-09 |
| GO:BP | GO:1902969 | mitotic DNA replication | 10 | 17 | 1.933e-09 |
| GO:BP | GO:0140694 | membraneless organelle assembly | 43 | 391 | 2.034e-09 |
| GO:BP | GO:0030261 | chromosome condensation | 13 | 34 | 2.460e-09 |
| GO:BP | GO:0000022 | mitotic spindle elongation | 8 | 10 | 4.131e-09 |
| GO:BP | GO:0090231 | regulation of spindle checkpoint | 11 | 24 | 6.921e-09 |
| GO:BP | GO:0071459 | protein localization to chromosome, centromeric region | 12 | 30 | 7.066e-09 |
| GO:BP | GO:0051716 | cellular response to stimulus | 245 | 4968 | 9.448e-09 |
| GO:BP | GO:0000281 | mitotic cytokinesis | 19 | 89 | 9.782e-09 |
| GO:BP | GO:0033043 | regulation of organelle organization | 76 | 1002 | 9.782e-09 |
| GO:BP | GO:0032465 | regulation of cytokinesis | 18 | 80 | 1.141e-08 |
| GO:BP | GO:0000910 | cytokinesis | 26 | 169 | 1.141e-08 |
| GO:BP | GO:1901970 | positive regulation of mitotic sister chromatid separation | 10 | 20 | 1.522e-08 |
| GO:BP | GO:0010639 | negative regulation of organelle organization | 36 | 312 | 1.967e-08 |
| GO:BP | GO:1901993 | regulation of meiotic cell cycle phase transition | 7 | 8 | 1.979e-08 |
| GO:BP | GO:0051255 | spindle midzone assembly | 8 | 12 | 3.903e-08 |
| GO:BP | GO:0051302 | regulation of cell division | 23 | 145 | 6.351e-08 |
| GO:BP | GO:0008315 | G2/MI transition of meiotic cell cycle | 6 | 6 | 6.988e-08 |
| GO:BP | GO:0007010 | cytoskeleton organization | 85 | 1230 | 6.988e-08 |
| GO:BP | GO:0090266 | regulation of mitotic cell cycle spindle assembly checkpoint | 10 | 23 | 8.045e-08 |
| GO:BP | GO:1903504 | regulation of mitotic spindle checkpoint | 10 | 23 | 8.045e-08 |
| GO:BP | GO:0065004 | protein-DNA complex assembly | 25 | 175 | 1.132e-07 |
| GO:BP | GO:0050896 | response to stimulus | 272 | 5825 | 1.329e-07 |
| GO:BP | GO:0032467 | positive regulation of cytokinesis | 12 | 38 | 1.492e-07 |
| GO:BP | GO:0035825 | homologous recombination | 13 | 46 | 1.543e-07 |
| GO:BP | GO:0007098 | centrosome cycle | 21 | 129 | 1.878e-07 |
| GO:BP | GO:0051445 | regulation of meiotic cell cycle | 13 | 47 | 2.035e-07 |
| GO:BP | GO:2000241 | regulation of reproductive process | 20 | 118 | 2.074e-07 |
| GO:BP | GO:0071824 | protein-DNA complex organization | 26 | 194 | 2.074e-07 |
| GO:BP | GO:0034502 | protein localization to chromosome | 19 | 107 | 2.221e-07 |
| GO:BP | GO:0034080 | CENP-A containing chromatin assembly | 7 | 10 | 2.463e-07 |
| GO:BP | GO:0031055 | chromatin remodeling at centromere | 7 | 10 | 2.463e-07 |
| GO:BP | GO:0016043 | cellular component organization | 248 | 5231 | 3.693e-07 |
| GO:BP | GO:0034501 | protein localization to kinetochore | 8 | 15 | 3.997e-07 |
| GO:BP | GO:0006271 | DNA strand elongation involved in DNA replication | 8 | 15 | 3.997e-07 |
| GO:BP | GO:1903083 | protein localization to condensed chromosome | 8 | 15 | 3.997e-07 |
| GO:BP | GO:0000077 | DNA damage checkpoint signaling | 19 | 112 | 4.629e-07 |
| GO:BP | GO:0033554 | cellular response to stress | 100 | 1609 | 5.096e-07 |
| GO:BP | GO:0061640 | cytoskeleton-dependent cytokinesis | 19 | 113 | 5.313e-07 |
| GO:BP | GO:0051052 | regulation of DNA metabolic process | 41 | 438 | 5.336e-07 |
| GO:BP | GO:0031023 | microtubule organizing center organization | 21 | 138 | 5.832e-07 |
| GO:BP | GO:0051447 | negative regulation of meiotic cell cycle | 7 | 11 | 6.143e-07 |
| GO:BP | GO:0007062 | sister chromatid cohesion | 13 | 52 | 7.001e-07 |
| GO:BP | GO:0044774 | mitotic DNA integrity checkpoint signaling | 15 | 73 | 1.027e-06 |
| GO:BP | GO:0008283 | cell population proliferation | 89 | 1397 | 1.161e-06 |
| GO:BP | GO:0045143 | homologous chromosome segregation | 11 | 37 | 1.164e-06 |
| GO:BP | GO:0051382 | kinetochore assembly | 8 | 17 | 1.320e-06 |
| GO:BP | GO:1905821 | positive regulation of chromosome condensation | 6 | 8 | 1.510e-06 |
| GO:BP | GO:0070192 | chromosome organization involved in meiotic cell cycle | 11 | 38 | 1.557e-06 |
| GO:BP | GO:0051653 | spindle localization | 13 | 56 | 1.749e-06 |
| GO:BP | GO:0010972 | negative regulation of G2/M transition of mitotic cell cycle | 14 | 66 | 1.840e-06 |
| GO:BP | GO:1902750 | negative regulation of cell cycle G2/M phase transition | 14 | 68 | 2.727e-06 |
| GO:BP | GO:0090232 | positive regulation of spindle checkpoint | 7 | 13 | 2.803e-06 |
| GO:BP | GO:0051781 | positive regulation of cell division | 14 | 69 | 3.271e-06 |
| GO:BP | GO:0007076 | mitotic chromosome condensation | 8 | 19 | 3.670e-06 |
| GO:BP | GO:0007144 | female meiosis I | 6 | 9 | 4.187e-06 |
| GO:BP | GO:0010971 | positive regulation of G2/M transition of mitotic cell cycle | 9 | 26 | 4.347e-06 |
| GO:BP | GO:0000082 | G1/S transition of mitotic cell cycle | 23 | 184 | 4.746e-06 |
| GO:BP | GO:0090306 | meiotic spindle assembly | 7 | 14 | 5.244e-06 |
| GO:BP | GO:0051293 | establishment of spindle localization | 12 | 52 | 5.709e-06 |
| GO:BP | GO:0000212 | meiotic spindle organization | 8 | 20 | 5.722e-06 |
| GO:BP | GO:2000242 | negative regulation of reproductive process | 11 | 43 | 5.858e-06 |
| GO:BP | GO:0044843 | cell cycle G1/S phase transition | 24 | 203 | 7.114e-06 |
| GO:BP | GO:0035556 | intracellular signal transduction | 128 | 2349 | 7.114e-06 |
| GO:BP | GO:0045835 | negative regulation of meiotic nuclear division | 5 | 6 | 8.516e-06 |
| GO:BP | GO:0044818 | mitotic G2/M transition checkpoint | 12 | 54 | 8.592e-06 |
| GO:BP | GO:0045005 | DNA-templated DNA replication maintenance of fidelity | 12 | 55 | 1.058e-05 |
| GO:BP | GO:1902751 | positive regulation of cell cycle G2/M phase transition | 9 | 29 | 1.189e-05 |
| GO:BP | GO:0071840 | cellular component organization or biogenesis | 248 | 5431 | 1.210e-05 |
| GO:BP | GO:0007131 | reciprocal meiotic recombination | 10 | 38 | 1.494e-05 |
| GO:BP | GO:0140527 | reciprocal homologous recombination | 10 | 38 | 1.494e-05 |
| GO:BP | GO:0007056 | spindle assembly involved in female meiosis | 6 | 11 | 1.979e-05 |
| GO:BP | GO:0044773 | mitotic DNA damage checkpoint signaling | 13 | 69 | 2.049e-05 |
| GO:BP | GO:0051338 | regulation of transferase activity | 35 | 398 | 2.208e-05 |
| GO:BP | GO:0051294 | establishment of spindle orientation | 10 | 40 | 2.458e-05 |
| GO:BP | GO:0051307 | meiotic chromosome separation | 5 | 7 | 2.725e-05 |
| GO:BP | GO:0060623 | regulation of chromosome condensation | 6 | 12 | 3.718e-05 |
| GO:BP | GO:0090267 | positive regulation of mitotic cell cycle spindle assembly checkpoint | 6 | 12 | 3.718e-05 |
| GO:BP | GO:0007057 | spindle assembly involved in female meiosis I | 4 | 4 | 3.774e-05 |
| GO:BP | GO:0045840 | positive regulation of mitotic nuclear division | 9 | 33 | 3.774e-05 |
| GO:BP | GO:0110030 | regulation of G2/MI transition of meiotic cell cycle | 4 | 4 | 3.774e-05 |
| GO:BP | GO:0051785 | positive regulation of nuclear division | 10 | 42 | 3.857e-05 |
| GO:BP | GO:0000079 | regulation of cyclin-dependent protein serine/threonine kinase activity | 12 | 63 | 4.554e-05 |
| GO:BP | GO:0042770 | signal transduction in response to DNA damage | 20 | 166 | 4.664e-05 |
| GO:BP | GO:0007292 | female gamete generation | 16 | 111 | 4.664e-05 |
| GO:BP | GO:0006468 | protein phosphorylation | 63 | 963 | 4.962e-05 |
| GO:BP | GO:0000076 | DNA replication checkpoint signaling | 7 | 19 | 5.638e-05 |
| GO:BP | GO:1901978 | positive regulation of cell cycle checkpoint | 7 | 19 | 5.638e-05 |
| GO:BP | GO:0046385 | deoxyribose phosphate biosynthetic process | 6 | 13 | 6.241e-05 |
| GO:BP | GO:1903490 | positive regulation of mitotic cytokinesis | 6 | 13 | 6.241e-05 |
| GO:BP | GO:0009265 | 2’-deoxyribonucleotide biosynthetic process | 6 | 13 | 6.241e-05 |
| GO:BP | GO:0009263 | deoxyribonucleotide biosynthetic process | 6 | 13 | 6.241e-05 |
| GO:BP | GO:0040020 | regulation of meiotic nuclear division | 7 | 20 | 8.204e-05 |
| GO:BP | GO:0007095 | mitotic G2 DNA damage checkpoint signaling | 9 | 37 | 9.959e-05 |
| GO:BP | GO:0040001 | establishment of mitotic spindle localization | 9 | 37 | 9.959e-05 |
| GO:BP | GO:1902412 | regulation of mitotic cytokinesis | 6 | 14 | 1.034e-04 |
| GO:BP | GO:0090235 | regulation of metaphase plate congression | 6 | 14 | 1.034e-04 |
| GO:BP | GO:0007276 | gamete generation | 39 | 505 | 1.156e-04 |
| GO:BP | GO:0031297 | replication fork processing | 10 | 48 | 1.300e-04 |
| GO:BP | GO:1902423 | regulation of attachment of mitotic spindle microtubules to kinetochore | 5 | 9 | 1.367e-04 |
| GO:BP | GO:0016310 | phosphorylation | 65 | 1044 | 1.625e-04 |
| GO:BP | GO:1902315 | nuclear cell cycle DNA replication initiation | 4 | 5 | 1.625e-04 |
| GO:BP | GO:1902975 | mitotic DNA replication initiation | 4 | 5 | 1.625e-04 |
| GO:BP | GO:0044785 | metaphase/anaphase transition of meiotic cell cycle | 4 | 5 | 1.625e-04 |
| GO:BP | GO:1901994 | negative regulation of meiotic cell cycle phase transition | 4 | 5 | 1.625e-04 |
| GO:BP | GO:1902292 | cell cycle DNA replication initiation | 4 | 5 | 1.625e-04 |
| GO:BP | GO:0000731 | DNA synthesis involved in DNA repair | 9 | 40 | 1.881e-04 |
| GO:BP | GO:0009314 | response to radiation | 30 | 351 | 1.996e-04 |
| GO:BP | GO:0071897 | DNA biosynthetic process | 18 | 154 | 2.057e-04 |
| GO:BP | GO:0048609 | multicellular organismal reproductive process | 43 | 598 | 2.174e-04 |
| GO:BP | GO:0045842 | positive regulation of mitotic metaphase/anaphase transition | 6 | 16 | 2.421e-04 |
| GO:BP | GO:1902101 | positive regulation of metaphase/anaphase transition of cell cycle | 6 | 16 | 2.421e-04 |
| GO:BP | GO:2001252 | positive regulation of chromosome organization | 14 | 100 | 2.500e-04 |
| GO:BP | GO:0051053 | negative regulation of DNA metabolic process | 15 | 114 | 2.644e-04 |
| GO:BP | GO:0090224 | regulation of spindle organization | 9 | 44 | 4.143e-04 |
| GO:BP | GO:0050789 | regulation of biological process | 336 | 8147 | 4.147e-04 |
| GO:BP | GO:0051987 | positive regulation of attachment of spindle microtubules to kinetochore | 5 | 11 | 4.374e-04 |
| GO:BP | GO:0010032 | meiotic chromosome condensation | 4 | 6 | 4.492e-04 |
| GO:BP | GO:0070925 | organelle assembly | 56 | 891 | 5.222e-04 |
| GO:BP | GO:0051128 | regulation of cellular component organization | 105 | 2008 | 5.542e-04 |
| GO:BP | GO:0022616 | DNA strand elongation | 8 | 36 | 6.169e-04 |
| GO:BP | GO:0009987 | cellular process | 456 | 11923 | 6.374e-04 |
| GO:BP | GO:0008284 | positive regulation of cell population proliferation | 43 | 629 | 6.931e-04 |
| GO:BP | GO:1904666 | regulation of ubiquitin protein ligase activity | 6 | 19 | 7.106e-04 |
| GO:BP | GO:0051347 | positive regulation of transferase activity | 21 | 218 | 7.190e-04 |
| GO:BP | GO:0042127 | regulation of cell population proliferation | 67 | 1148 | 8.340e-04 |
| GO:BP | GO:1901995 | positive regulation of meiotic cell cycle phase transition | 3 | 3 | 8.464e-04 |
| GO:BP | GO:0071163 | DNA replication preinitiation complex assembly | 3 | 3 | 8.464e-04 |
| GO:BP | GO:0110032 | positive regulation of G2/MI transition of meiotic cell cycle | 3 | 3 | 8.464e-04 |
| GO:BP | GO:0033316 | meiotic spindle assembly checkpoint signaling | 3 | 3 | 8.464e-04 |
| GO:BP | GO:1905832 | positive regulation of spindle assembly | 4 | 7 | 9.643e-04 |
| GO:BP | GO:0071900 | regulation of protein serine/threonine kinase activity | 19 | 190 | 9.767e-04 |
| GO:BP | GO:0045859 | regulation of protein kinase activity | 26 | 315 | 1.260e-03 |
| GO:BP | GO:0008156 | negative regulation of DNA replication | 6 | 21 | 1.283e-03 |
| GO:BP | GO:0010638 | positive regulation of organelle organization | 32 | 431 | 1.475e-03 |
| GO:BP | GO:0050790 | regulation of catalytic activity | 47 | 735 | 1.481e-03 |
| GO:BP | GO:0050794 | regulation of cellular process | 324 | 7899 | 1.487e-03 |
| GO:BP | GO:0060236 | regulation of mitotic spindle organization | 8 | 41 | 1.552e-03 |
| GO:BP | GO:0051129 | negative regulation of cellular component organization | 40 | 592 | 1.574e-03 |
| GO:BP | GO:0001833 | inner cell mass cell proliferation | 5 | 14 | 1.576e-03 |
| GO:BP | GO:0007064 | mitotic sister chromatid cohesion | 7 | 31 | 1.604e-03 |
| GO:BP | GO:0062033 | positive regulation of mitotic sister chromatid segregation | 4 | 8 | 1.766e-03 |
| GO:BP | GO:0033313 | meiotic cell cycle checkpoint signaling | 4 | 8 | 1.766e-03 |
| GO:BP | GO:1902425 | positive regulation of attachment of mitotic spindle microtubules to kinetochore | 4 | 8 | 1.766e-03 |
| GO:BP | GO:0009157 | deoxyribonucleoside monophosphate biosynthetic process | 4 | 8 | 1.766e-03 |
| GO:BP | GO:1904776 | regulation of protein localization to cell cortex | 4 | 8 | 1.766e-03 |
| GO:BP | GO:0008150 | biological_process | 462 | 12194 | 1.826e-03 |
| GO:BP | GO:0007165 | signal transduction | 178 | 3916 | 1.915e-03 |
| GO:BP | GO:0000132 | establishment of mitotic spindle orientation | 7 | 32 | 1.929e-03 |
| GO:BP | GO:0071478 | cellular response to radiation | 16 | 153 | 2.068e-03 |
| GO:BP | GO:0007154 | cell communication | 192 | 4292 | 2.158e-03 |
| GO:BP | GO:0051299 | centrosome separation | 5 | 15 | 2.191e-03 |
| GO:BP | GO:0071695 | anatomical structure maturation | 17 | 170 | 2.203e-03 |
| GO:BP | GO:0032886 | regulation of microtubule-based process | 20 | 222 | 2.466e-03 |
| GO:BP | GO:0051298 | centrosome duplication | 10 | 69 | 2.728e-03 |
| GO:BP | GO:0009394 | 2’-deoxyribonucleotide metabolic process | 7 | 34 | 2.823e-03 |
| GO:BP | GO:1902102 | regulation of metaphase/anaphase transition of meiotic cell cycle | 3 | 4 | 2.851e-03 |
| GO:BP | GO:1900264 | positive regulation of DNA-directed DNA polymerase activity | 4 | 9 | 2.851e-03 |
| GO:BP | GO:1905784 | regulation of anaphase-promoting complex-dependent catabolic process | 3 | 4 | 2.851e-03 |
| GO:BP | GO:1905133 | negative regulation of meiotic chromosome separation | 3 | 4 | 2.851e-03 |
| GO:BP | GO:1990918 | double-strand break repair involved in meiotic recombination | 3 | 4 | 2.851e-03 |
| GO:BP | GO:0044779 | meiotic spindle checkpoint signaling | 3 | 4 | 2.851e-03 |
| GO:BP | GO:2000104 | negative regulation of DNA-templated DNA replication | 4 | 9 | 2.851e-03 |
| GO:BP | GO:1902103 | negative regulation of metaphase/anaphase transition of meiotic cell cycle | 3 | 4 | 2.851e-03 |
| GO:BP | GO:0000912 | assembly of actomyosin apparatus involved in cytokinesis | 4 | 9 | 2.851e-03 |
| GO:BP | GO:0000915 | actomyosin contractile ring assembly | 4 | 9 | 2.851e-03 |
| GO:BP | GO:1905132 | regulation of meiotic chromosome separation | 3 | 4 | 2.851e-03 |
| GO:BP | GO:1904668 | positive regulation of ubiquitin protein ligase activity | 4 | 9 | 2.851e-03 |
| GO:BP | GO:0009262 | deoxyribonucleotide metabolic process | 7 | 35 | 3.252e-03 |
| GO:BP | GO:0019692 | deoxyribose phosphate metabolic process | 7 | 35 | 3.252e-03 |
| GO:BP | GO:0023052 | signaling | 190 | 4280 | 3.533e-03 |
| GO:BP | GO:0043549 | regulation of kinase activity | 26 | 339 | 3.567e-03 |
| GO:BP | GO:0010212 | response to ionizing radiation | 14 | 131 | 3.976e-03 |
| GO:BP | GO:0032506 | cytokinetic process | 8 | 48 | 4.303e-03 |
| GO:BP | GO:0044837 | actomyosin contractile ring organization | 4 | 10 | 4.469e-03 |
| GO:BP | GO:0072697 | protein localization to cell cortex | 4 | 10 | 4.469e-03 |
| GO:BP | GO:0033314 | mitotic DNA replication checkpoint signaling | 4 | 10 | 4.469e-03 |
| GO:BP | GO:0007140 | male meiotic nuclear division | 6 | 27 | 4.916e-03 |
| GO:BP | GO:0007129 | homologous chromosome pairing at meiosis | 6 | 27 | 4.916e-03 |
| GO:BP | GO:0070507 | regulation of microtubule cytoskeleton organization | 15 | 150 | 4.916e-03 |
| GO:BP | GO:0009162 | deoxyribonucleoside monophosphate metabolic process | 5 | 18 | 5.156e-03 |
| GO:BP | GO:0045740 | positive regulation of DNA replication | 7 | 38 | 5.336e-03 |
| GO:BP | GO:0006338 | chromatin remodeling | 37 | 570 | 5.409e-03 |
| GO:BP | GO:0065007 | biological regulation | 337 | 8399 | 5.934e-03 |
| GO:BP | GO:0048144 | fibroblast proliferation | 11 | 91 | 6.015e-03 |
| GO:BP | GO:2000045 | regulation of G1/S transition of mitotic cell cycle | 14 | 137 | 6.051e-03 |
| GO:BP | GO:0007099 | centriole replication | 7 | 39 | 6.180e-03 |
| GO:BP | GO:0036297 | interstrand cross-link repair | 7 | 39 | 6.180e-03 |
| GO:BP | GO:1902806 | regulation of cell cycle G1/S phase transition | 15 | 154 | 6.324e-03 |
| GO:BP | GO:0046073 | dTMP metabolic process | 3 | 5 | 6.373e-03 |
| GO:BP | GO:0090402 | oncogene-induced cell senescence | 3 | 5 | 6.373e-03 |
| GO:BP | GO:0016321 | female meiosis chromosome segregation | 3 | 5 | 6.373e-03 |
| GO:BP | GO:0030010 | establishment of cell polarity | 14 | 138 | 6.373e-03 |
| GO:BP | GO:0003006 | developmental process involved in reproduction | 40 | 640 | 6.515e-03 |
| GO:BP | GO:0006950 | response to stress | 131 | 2807 | 7.010e-03 |
| GO:BP | GO:2000243 | positive regulation of reproductive process | 8 | 52 | 7.033e-03 |
| GO:BP | GO:0031109 | microtubule polymerization or depolymerization | 13 | 125 | 7.869e-03 |
| GO:BP | GO:1902808 | positive regulation of cell cycle G1/S phase transition | 8 | 53 | 7.977e-03 |
| GO:BP | GO:0001832 | blastocyst growth | 5 | 20 | 8.287e-03 |
| GO:BP | GO:0098534 | centriole assembly | 7 | 42 | 9.473e-03 |
| GO:BP | GO:0048146 | positive regulation of fibroblast proliferation | 7 | 42 | 9.473e-03 |
| GO:BP | GO:0071479 | cellular response to ionizing radiation | 9 | 68 | 9.742e-03 |
| GO:BP | GO:0007019 | microtubule depolymerization | 7 | 43 | 1.087e-02 |
| GO:BP | GO:0009411 | response to UV | 14 | 146 | 1.087e-02 |
| GO:BP | GO:0006335 | DNA replication-dependent chromatin assembly | 3 | 6 | 1.179e-02 |
| GO:BP | GO:0009221 | pyrimidine deoxyribonucleotide biosynthetic process | 3 | 6 | 1.179e-02 |
| GO:BP | GO:0090166 | Golgi disassembly | 3 | 6 | 1.179e-02 |
| GO:BP | GO:0014831 | gastro-intestinal system smooth muscle contraction | 3 | 6 | 1.179e-02 |
| GO:BP | GO:0042148 | DNA strand invasion | 3 | 6 | 1.179e-02 |
| GO:BP | GO:0104004 | cellular response to environmental stimulus | 21 | 273 | 1.184e-02 |
| GO:BP | GO:0071214 | cellular response to abiotic stimulus | 21 | 273 | 1.184e-02 |
| GO:BP | GO:0007100 | mitotic centrosome separation | 4 | 13 | 1.243e-02 |
| GO:BP | GO:0009130 | pyrimidine nucleoside monophosphate biosynthetic process | 4 | 13 | 1.243e-02 |
| GO:BP | GO:0031145 | anaphase-promoting complex-dependent catabolic process | 5 | 22 | 1.266e-02 |
| GO:BP | GO:0051438 | regulation of ubiquitin-protein transferase activity | 6 | 34 | 1.614e-02 |
| GO:BP | GO:2000105 | positive regulation of DNA-templated DNA replication | 4 | 14 | 1.675e-02 |
| GO:BP | GO:1905325 | regulation of meiosis I spindle assembly checkpoint | 2 | 2 | 1.676e-02 |
| GO:BP | GO:1990426 | mitotic recombination-dependent replication fork processing | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0031619 | homologous chromosome orientation in meiotic metaphase I | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0031507 | heterochromatin formation | 11 | 104 | 1.676e-02 |
| GO:BP | GO:1990505 | mitotic DNA replication maintenance of fidelity | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0140274 | repair of kinetochore microtubule attachment defect | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0006939 | smooth muscle contraction | 9 | 74 | 1.676e-02 |
| GO:BP | GO:1902298 | cell cycle DNA replication maintenance of fidelity | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0140273 | repair of mitotic kinetochore microtubule attachment defect | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0014846 | esophagus smooth muscle contraction | 2 | 2 | 1.676e-02 |
| GO:BP | GO:1905318 | meiosis I spindle assembly checkpoint signaling | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0060631 | regulation of meiosis I | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0110029 | negative regulation of meiosis I | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0099607 | lateral attachment of mitotic spindle microtubules to kinetochore | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0071881 | adenylate cyclase-inhibiting adrenergic receptor signaling pathway | 2 | 2 | 1.676e-02 |
| GO:BP | GO:0001556 | oocyte maturation | 5 | 24 | 1.826e-02 |
| GO:BP | GO:0009176 | pyrimidine deoxyribonucleoside monophosphate metabolic process | 3 | 7 | 1.870e-02 |
| GO:BP | GO:0043085 | positive regulation of catalytic activity | 28 | 425 | 1.897e-02 |
| GO:BP | GO:0031100 | animal organ regeneration | 7 | 48 | 1.934e-02 |
| GO:BP | GO:0032147 | activation of protein kinase activity | 7 | 48 | 1.934e-02 |
| GO:BP | GO:0009792 | embryo development ending in birth or egg hatching | 34 | 552 | 1.940e-02 |
| GO:BP | GO:2000780 | negative regulation of double-strand break repair | 6 | 36 | 2.045e-02 |
| GO:BP | GO:0001932 | regulation of protein phosphorylation | 36 | 597 | 2.045e-02 |
| GO:BP | GO:0006301 | postreplication repair | 6 | 36 | 2.045e-02 |
| GO:BP | GO:0048469 | cell maturation | 12 | 124 | 2.093e-02 |
| GO:BP | GO:0021700 | developmental maturation | 18 | 231 | 2.145e-02 |
| GO:BP | GO:0048856 | anatomical structure development | 182 | 4234 | 2.285e-02 |
| GO:BP | GO:0072528 | pyrimidine-containing compound biosynthetic process | 6 | 37 | 2.335e-02 |
| GO:BP | GO:0009124 | nucleoside monophosphate biosynthetic process | 6 | 37 | 2.335e-02 |
| GO:BP | GO:0045814 | negative regulation of gene expression, epigenetic | 13 | 143 | 2.374e-02 |
| GO:BP | GO:0048519 | negative regulation of biological process | 174 | 4029 | 2.458e-02 |
| GO:BP | GO:0048232 | male gamete generation | 25 | 372 | 2.461e-02 |
| GO:BP | GO:0065009 | regulation of molecular function | 61 | 1174 | 2.482e-02 |
| GO:BP | GO:0019985 | translesion synthesis | 5 | 26 | 2.525e-02 |
| GO:BP | GO:0071392 | cellular response to estradiol stimulus | 5 | 26 | 2.525e-02 |
| GO:BP | GO:0051446 | positive regulation of meiotic cell cycle | 4 | 16 | 2.573e-02 |
| GO:BP | GO:0007096 | regulation of exit from mitosis | 4 | 16 | 2.573e-02 |
| GO:BP | GO:0048313 | Golgi inheritance | 4 | 16 | 2.573e-02 |
| GO:BP | GO:0048308 | organelle inheritance | 4 | 16 | 2.573e-02 |
| GO:BP | GO:0048608 | reproductive structure development | 17 | 217 | 2.592e-02 |
| GO:BP | GO:0045738 | negative regulation of DNA repair | 6 | 38 | 2.603e-02 |
| GO:BP | GO:0046605 | regulation of centrosome cycle | 7 | 51 | 2.609e-02 |
| GO:BP | GO:0009628 | response to abiotic stimulus | 48 | 877 | 2.669e-02 |
| GO:BP | GO:1903251 | multi-ciliated epithelial cell differentiation | 3 | 8 | 2.687e-02 |
| GO:BP | GO:0007077 | mitotic nuclear membrane disassembly | 3 | 8 | 2.687e-02 |
| GO:BP | GO:0046602 | regulation of mitotic centrosome separation | 3 | 8 | 2.687e-02 |
| GO:BP | GO:0022607 | cellular component assembly | 117 | 2563 | 2.839e-02 |
| GO:BP | GO:0061458 | reproductive system development | 17 | 220 | 2.924e-02 |
| GO:BP | GO:0050918 | positive chemotaxis | 6 | 39 | 2.924e-02 |
| GO:BP | GO:0032502 | developmental process | 194 | 4584 | 2.995e-02 |
| GO:BP | GO:0001824 | blastocyst development | 10 | 98 | 3.151e-02 |
| GO:BP | GO:0051443 | positive regulation of ubiquitin-protein transferase activity | 4 | 17 | 3.151e-02 |
| GO:BP | GO:0009129 | pyrimidine nucleoside monophosphate metabolic process | 4 | 17 | 3.151e-02 |
| GO:BP | GO:0045137 | development of primary sexual characteristics | 14 | 167 | 3.241e-02 |
| GO:BP | GO:0051054 | positive regulation of DNA metabolic process | 19 | 261 | 3.248e-02 |
| GO:BP | GO:0042325 | regulation of phosphorylation | 37 | 639 | 3.248e-02 |
| GO:BP | GO:0006325 | chromatin organization | 40 | 706 | 3.260e-02 |
| GO:BP | GO:0006221 | pyrimidine nucleotide biosynthetic process | 5 | 28 | 3.346e-02 |
| GO:BP | GO:0048513 | animal organ development | 101 | 2176 | 3.517e-02 |
| GO:BP | GO:0110025 | DNA strand resection involved in replication fork processing | 3 | 9 | 3.764e-02 |
| GO:BP | GO:0046601 | positive regulation of centriole replication | 3 | 9 | 3.764e-02 |
| GO:BP | GO:0035860 | glial cell-derived neurotrophic factor receptor signaling pathway | 3 | 9 | 3.764e-02 |
| GO:BP | GO:0010458 | exit from mitosis | 5 | 29 | 3.876e-02 |
| GO:BP | GO:0043009 | chordate embryonic development | 32 | 537 | 3.921e-02 |
| GO:BP | GO:0072698 | protein localization to microtubule cytoskeleton | 7 | 56 | 4.222e-02 |
| GO:BP | GO:0051296 | establishment of meiotic spindle orientation | 2 | 3 | 4.224e-02 |
| GO:BP | GO:1990086 | lens fiber cell apoptotic process | 2 | 3 | 4.224e-02 |
| GO:BP | GO:0034421 | post-translational protein acetylation | 2 | 3 | 4.224e-02 |
| GO:BP | GO:0051754 | meiotic sister chromatid cohesion, centromeric | 2 | 3 | 4.224e-02 |
| GO:BP | GO:0009177 | pyrimidine deoxyribonucleoside monophosphate biosynthetic process | 2 | 3 | 4.224e-02 |
| GO:BP | GO:0006231 | dTMP biosynthetic process | 2 | 3 | 4.224e-02 |
| GO:BP | GO:0008584 | male gonad development | 10 | 103 | 4.295e-02 |
| GO:BP | GO:0048523 | negative regulation of cellular process | 167 | 3904 | 4.372e-02 |
| GO:BP | GO:1900087 | positive regulation of G1/S transition of mitotic cell cycle | 6 | 43 | 4.541e-02 |
| GO:BP | GO:0046546 | development of primary male sexual characteristics | 10 | 104 | 4.570e-02 |
| GO:BP | GO:0009219 | pyrimidine deoxyribonucleotide metabolic process | 4 | 19 | 4.574e-02 |
| GO:BP | GO:0048522 | positive regulation of cellular process | 186 | 4416 | 4.608e-02 |
| GO:BP | GO:0061842 | microtubule organizing center localization | 5 | 31 | 4.988e-02 |
| GO:BP | GO:0051642 | centrosome localization | 5 | 31 | 4.988e-02 |
| GO:BP | GO:0090169 | regulation of spindle assembly | 5 | 31 | 4.988e-02 |
| GO:BP | GO:0070601 | centromeric sister chromatid cohesion | 3 | 10 | 4.988e-02 |
| GO:BP | GO:0072711 | cellular response to hydroxyurea | 3 | 10 | 4.988e-02 |
| GO:BP | GO:0071168 | protein localization to chromatin | 6 | 44 | 4.991e-02 |
| KEGG | KEGG:04110 | Cell cycle | 46 | 152 | 6.322e-28 |
| KEGG | KEGG:03030 | DNA replication | 16 | 35 | 1.523e-12 |
| KEGG | KEGG:03460 | Fanconi anemia pathway | 12 | 49 | 8.690e-06 |
| KEGG | KEGG:04114 | Oocyte meiosis | 17 | 110 | 2.154e-05 |
| KEGG | KEGG:04914 | Progesterone-mediated oocyte maturation | 15 | 88 | 2.299e-05 |
| KEGG | KEGG:03440 | Homologous recombination | 10 | 39 | 3.192e-05 |
| KEGG | KEGG:04115 | p53 signaling pathway | 12 | 67 | 1.346e-04 |
| KEGG | KEGG:04814 | Motor proteins | 17 | 150 | 8.033e-04 |
| KEGG | KEGG:04218 | Cellular senescence | 16 | 143 | 1.434e-03 |
| KEGG | KEGG:05166 | Human T-cell leukemia virus 1 infection | 17 | 177 | 5.108e-03 |
| KEGG | KEGG:05206 | MicroRNAs in cancer | 15 | 151 | 7.504e-03 |
| KEGG | KEGG:03410 | Base excision repair | 7 | 43 | 1.533e-02 |
| KEGG | KEGG:03430 | Mismatch repair | 5 | 22 | 1.579e-02 |
| KEGG | KEGG:00240 | Pyrimidine metabolism | 7 | 44 | 1.579e-02 |
| KEGG | KEGG:04060 | Cytokine-cytokine receptor interaction | 11 | 103 | 1.831e-02 |
| KEGG | KEGG:01232 | Nucleotide metabolism | 8 | 67 | 3.751e-02 |
| KEGG | KEGG:04151 | PI3K-Akt signaling pathway | 19 | 260 | 3.751e-02 |
#GO:BP
table_motif2_genes_GOBP_RUV <- table_motif2_GOKEGG_genes_RUV %>%
dplyr::filter(source=="GO:BP") %>%
dplyr::select(p_value, term_name, intersection_size) %>%
dplyr::slice_min(., n=20, order_by=p_value) %>%
mutate(log_val = -log10(p_value))
table_motif2_genes_GOBP_RUV %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
geom_point(aes(size = intersection_size)) +
ggtitle("M2 Enriched GO:BP Terms RUVs")+
xlab(expression("-log"[10]~"p-value"))+
guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
ylab("GO:BP term")+
scale_y_discrete(labels = scales::label_wrap(30))+
theme_bw()+
theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
axis.title = element_text(size = 15, colour = "black"),
axis.ticks = element_line(linewidth = 1.5),
axis.line = element_line(linewidth = 1.5),
axis.text = element_text(size = 10, colour = "black", angle = 0),
strip.text = element_text(size = 15, colour = "black", face = "bold"))
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#KEGG
table_motif2_genes_KEGG_RUV <- table_motif2_GOKEGG_genes_RUV %>%
dplyr::filter(source=="KEGG") %>%
dplyr::select(p_value, term_name, intersection_size) %>%
dplyr::slice_min(., n=20, order_by=p_value) %>%
mutate(log_val = -log10(p_value))
table_motif2_genes_KEGG_RUV %>% ggplot(., aes(x = log_val, y = reorder(term_name, p_value), col= intersection_size)) +
geom_point(aes(size = intersection_size)) +
ggtitle("M2 DEGs Enriched KEGG Terms RUVs")+
xlab(expression("-log"[10]~"p-value"))+
guides(col="none", size= guide_legend(title = "# of intersected \n terms"))+
ylab("KEGG term")+
scale_y_discrete(labels = scales::label_wrap(30))+
theme_custom()+
theme(plot.title = element_text(size = rel(1.5), hjust = 0.5),
axis.title = element_text(size = 15, colour = "black"),
axis.ticks = element_line(linewidth = 1.5),
axis.line = element_line(linewidth = 1.5),
axis.text = element_text(size = 10, colour = "black", angle = 0),
strip.text = element_text(size = 15, colour = "black", face = "bold"))
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#after finalizing this analysis, plot Figure 3E + 3F
kegg_m1_plot <- table_motif1_genes_KEGG_RUV %>%
ggplot(aes(x = log_val, y = reorder(term_name, p_value))) +
geom_point() +
ggtitle("Enriched Pathways: Acute") +
xlab(expression("-log"[10]~"adj. p-value")) +
ylab("KEGG Term") +
scale_y_discrete(labels = scales::label_wrap(30)) +
theme_custom()+
theme(axis.line = element_blank(),
panel.border = element_rect(
color = "black",
fill = NA,
linewidth = 1
),
axis.ticks = element_line(linewidth = .5),
legend.position = "none",
)
kegg_m2_plot <- table_motif2_genes_KEGG_RUV %>%
ggplot(aes(x = log_val, y = reorder(term_name, p_value))) +
geom_point() +
ggtitle("Enriched Pathways: Chronic") +
xlab(expression("-log"[10]~"adj. p-value")) +
ylab("KEGG Term") +
scale_y_discrete(labels = scales::label_wrap(30)) +
theme_custom()+
theme(axis.line = element_blank(),
panel.border = element_rect(
color = "black",
fill = NA,
linewidth = 1
),
axis.ticks = element_line(linewidth = .5),
legend.position = "none",
)
print(kegg_m1_plot)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
print(kegg_m2_plot)
| Version | Author | Date |
|---|---|---|
| 7f22593 | emmapfort | 2026-01-05 |
#now save these as pdfs
#acute cluster (motif1)
# cairo_pdf(
# file.path(output_folder, "KEGG_Recovered_UpdateFig3_EMP.pdf"),
# width = 6,
# height = 8
# )
# print(kegg_m1_plot)
# dev.off()
#chronic cluster (motif2)
# cairo_pdf(
# file.path(output_folder, "KEGG_Sustained_UpdateFig3_EMP.pdf"),
# width = 6,
# height = 8
# )
# print(kegg_m2_plot)
# dev.off()
sessionInfo()R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22000)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8
[2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
time zone: America/Chicago
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] edgeR_4.4.0 limma_3.62.1 gprofiler2_0.2.3
[4] ggfortify_0.4.17 eulerr_7.0.2 ggrastr_1.0.2
[7] ggVennDiagram_1.5.2 readxl_1.4.5 lubridate_1.9.4
[10] forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4
[13] purrr_1.0.4 readr_2.1.5 tidyr_1.3.1
[16] tibble_3.2.1 ggplot2_3.5.2 tidyverse_2.0.0
[19] workflowr_1.7.1
loaded via a namespace (and not attached):
[1] gtable_0.3.6 beeswarm_0.4.0 xfun_0.52 bslib_0.9.0
[5] htmlwidgets_1.6.4 processx_3.8.6 lattice_0.22-6 callr_3.7.6
[9] tzdb_0.5.0 crosstalk_1.2.1 bitops_1.0-9 vctrs_0.6.5
[13] tools_4.4.2 ps_1.9.1 generics_0.1.4 pkgconfig_2.0.3
[17] data.table_1.17.0 RColorBrewer_1.1-3 lifecycle_1.0.4 compiler_4.4.2
[21] farver_2.1.2 git2r_0.36.2 statmod_1.5.0 getPass_0.2-4
[25] vipor_0.4.7 httpuv_1.6.16 htmltools_0.5.8.1 sass_0.4.10
[29] RCurl_1.98-1.17 lazyeval_0.2.2 yaml_2.3.10 plotly_4.10.4
[33] later_1.4.2 pillar_1.10.2 jquerylib_0.1.4 whisker_0.4.1
[37] cachem_1.1.0 mime_0.13 locfit_1.5-9.12 tidyselect_1.2.1
[41] digest_0.6.37 stringi_1.8.7 labeling_0.4.3 rprojroot_2.0.4
[45] fastmap_1.2.0 grid_4.4.2 colorspace_2.1-1 cli_3.6.3
[49] magrittr_2.0.3 utf8_1.2.5 withr_3.0.2 scales_1.4.0
[53] promises_1.3.2 ggbeeswarm_0.7.2 timechange_0.3.0 rmarkdown_2.29
[57] httr_1.4.7 gridExtra_2.3 cellranger_1.1.0 hms_1.1.3
[61] kableExtra_1.4.0 shiny_1.10.0 evaluate_1.0.3 knitr_1.50
[65] viridisLite_0.4.2 rlang_1.1.6 Rcpp_1.0.14 xtable_1.8-4
[69] glue_1.8.0 xml2_1.3.8 svglite_2.1.3 rstudioapi_0.17.1
[73] jsonlite_2.0.0 R6_2.6.1 systemfonts_1.2.2 fs_1.6.6