Signal Site analysis

Last updated: 2019-07-31

Checks: 6 1

Knit directory: apaQTL/analysis/

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File	Version	Author	Date	Message
Rmd	589abea	brimittleman	2019-07-31	paper figs
html	1a928ed	brimittleman	2019-07-17	Build site.
Rmd	07e766f	brimittleman	2019-07-17	3 color signal stie plot
html	16e4212	brimittleman	2019-07-17	Build site.
Rmd	64bcc48	brimittleman	2019-07-17	fix plots meeting 7.15
html	96d85de	brimittleman	2019-07-07	Build site.
Rmd	4a51b04	brimittleman	2019-07-07	modify figures
html	6b0fbce	brimittleman	2019-06-21	Build site.
Rmd	d5ec3ba	brimittleman	2019-06-21	change colors
html	bfa47ca	brimittleman	2019-06-18	Build site.
Rmd	01f1f1d	brimittleman	2019-06-18	write out sites with ss
html	9c1dd66	brimittleman	2019-06-13	Build site.
html	ef7ddfe	brimittleman	2019-04-27	Build site.
Rmd	29464ab	brimittleman	2019-04-27	flip axis
html	4eb21ab	brimittleman	2019-04-26	Build site.
Rmd	fb7b995	brimittleman	2019-04-26	add proportion with site analysis
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Rmd	4febc15	brimittleman	2019-04-24	return to original SAF
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Rmd	6dc25d8	brimittleman	2019-04-24	update after SAF bug
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Rmd	76900e4	brimittleman	2019-04-24	add plots after parsing for 1 site per
html	12d1cb0	brimittleman	2019-04-23	Build site.
Rmd	e985ecd	brimittleman	2019-04-23	add initial plot
html	214c05c	brimittleman	2019-04-23	Build site.
Rmd	27b11e3	brimittleman	2019-04-23	start signal site analysis

library(seqLogo)

Loading required package: grid

library(tidyverse)

── Attaching packages ──────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──

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library(RColorBrewer)
library(workflowr)

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Run ?workflowr for help getting started

library(reshape2)


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library(gplots)


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library(cowplot)


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In this analysis I will plot the distribution of signal sites upstream of the PAS I have found.

First I use a python script to make a bed file with the 100 base pairs upsream of the PAS:

module load Anaconda3
source activate three-prime-env
mkdir ../data/SignalSiteFiles
python Upstream100Bases_general.py ../data/PAS/APAPAS_GeneLocAnno.5perc.bed ../data/SignalSiteFiles/APAPAS_100up.bed

Now I use bedtools nuc to get the sequence for each of these regions:

sbatch getSeq100up.sh

I can now run the DistPAS2Sig.py which will give me the location for the signal site for each PAS.I am running this with the 12 most common PAS signal sites.

sbatch run_distPAS2Sig.sh

Upload all of the results:

Loc_AATAAA= read.table("../data/SignalSiteFiles/Loc_AATAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="AATAAA")
Loc_AAAAAG= read.table("../data/SignalSiteFiles/Loc_AAAAAG_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="AAAAAG")
Loc_AATACA= read.table("../data/SignalSiteFiles/Loc_AATACA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="AATACA")
Loc_AATAGA= read.table("../data/SignalSiteFiles/Loc_AATAGA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="AATAGA")
Loc_AATATA= read.table("../data/SignalSiteFiles/Loc_AATATA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="AATATA")
Loc_ACTAAA= read.table("../data/SignalSiteFiles/Loc_ACTAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="ACTAAA")
Loc_AGTAAA= read.table("../data/SignalSiteFiles/Loc_AGTAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="AGTAAA")
Loc_ATTAAA= read.table("../data/SignalSiteFiles/Loc_ATTAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="ATTAAA")
Loc_CATAAA= read.table("../data/SignalSiteFiles/Loc_CATAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="CATAAA")
Loc_GATAAA= read.table("../data/SignalSiteFiles/Loc_GATAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="GATAAA")
Loc_TATAAA= read.table("../data/SignalSiteFiles/Loc_TATAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="TATAAA")
Loc_AAAAAA= read.table("../data/SignalSiteFiles/Loc_AAAAAA_Distance2end.txt", header=F, col.names =c( "PAS", "Distance2PAS")) %>% mutate(Site="AAAAAA")

Join these together:

AllsiteDF=as.data.frame(rbind(Loc_AATAAA,Loc_AAAAAG,Loc_AATACA,Loc_AATAGA,Loc_AATATA,Loc_ACTAAA,Loc_AGTAAA,Loc_ATTAAA, Loc_GATAAA,Loc_TATAAA,Loc_CATAAA, Loc_AAAAAA))

colourCount = length(unique(AllsiteDF$Site))
getPalette = colorRampPalette(brewer.pal(8, "Set1"))

AllsiteDF_sep = AllsiteDF %>% separate(PAS, int=c("GenePeak", "Location"), sep="_")
ggplot(AllsiteDF_sep, aes(x=Distance2PAS, by=Site, col=Site)) + stat_ecdf() + facet_wrap(~Location)

Version	Author	Date
96d85de	brimittleman	2019-07-07

Check to see if any PAS have more than one signal site detected:

AllsiteDFmultsites=AllsiteDF %>% group_by(PAS) %>% mutate(nSites=n()) %>% filter(nSites>1)

First take the perfect match within 50 bp then use the closest.

Write out the AllSite in order to use it in the chooseSignalSite.py script:

write.table(AllsiteDF, file="../data/SignalSiteFiles/AllSignalSite.txt", quote=F, col.names = F, row.names = F, sep="\t")

python chooseSignalSite.py ../data/SignalSiteFiles/AllSignalSite.txt ../data/SignalSiteFiles/AllSignalSite_1perPAS.txt

AllsiteDF_1per=read.table(file="../data/SignalSiteFiles/AllSignalSite_1perPAS.txt", col.names = colnames(AllsiteDF)) %>% mutate(NegCount=-1*as.integer(as.character(Distance2PAS)))

Plot

dist2signalsiteplot=ggplot(AllsiteDF_1per, aes(group=Site, x=NegCount, fill=Site)) + geom_histogram(position="stack",bins=50 ) + labs(x="Distance from PAS", y="N annotated Sites", title="Location of annotated signal sites")  +  scale_fill_manual(values = getPalette(colourCount))
dist2signalsiteplot

Version	Author	Date
96d85de	brimittleman	2019-07-07
26058a5	brimittleman	2019-04-24

ggsave(dist2signalsiteplot, file="../output/SignalSitePlot.png")

Saving 7 x 5 in image

Plot with proportion:

allPAS=read.table("../data/PAS/APAPAS_GeneLocAnno.5perc.bed", stringsAsFactors = F, col.names = c("chr","start","end","PAS","score","strand"))

AllsiteDF_1per_prop= AllsiteDF_1per %>% group_by(Site,NegCount) %>% summarise(CountperPos=n()) %>% mutate(TotCount=sum(CountperPos),prop=CountperPos/nrow(allPAS))

Plot with prop:

dist2signalsiteplotprop=ggplot(AllsiteDF_1per_prop, aes(group=Site, x=NegCount,y=prop, fill=Site)) + geom_histogram(position="stack",bins=50,stat="identity" ) + labs(x="Distance from PAS", y="Proportion of annotated Sites", title="Location of annotated signal sites",fill="Site Sequence") +  scale_fill_manual(values = getPalette(colourCount))+ theme(text = element_text(size=20, face="bold"),axis.text.x = element_text(size = 16),axis.text.y = element_text(size = 16), legend.position = "bottom",plot.title = element_text(size=22))+ guides(fill=guide_legend(nrow=3,byrow=TRUE))

Warning: Ignoring unknown parameters: binwidth, bins, pad

dist2signalsiteplotprop

Version	Author	Date
96d85de	brimittleman	2019-07-07

nrow(AllsiteDF_1per)/nrow(allPAS)

[1] 0.5462321

Seperate by location:

AllsiteDF_1per_sep= AllsiteDF_1per %>%separate(PAS, int=c("GenePeak", "Location"), sep="_")

dist2signalsiteplot_byloc=ggplot(AllsiteDF_1per_sep, aes(group=Site, x=NegCount, fill=Site)) + geom_histogram(position="stack",bins=50 ) + labs(x="Distance from PAS", y="N annotated Sites", title="Location of annotated signal sites") + facet_wrap(~Location)+  scale_fill_manual(values = getPalette(colourCount))

dist2signalsiteplot_byloc

Version	Author	Date
96d85de	brimittleman	2019-07-07
9c1dd66	brimittleman	2019-06-13
4eb21ab	brimittleman	2019-04-26

ggsave(dist2signalsiteplot_byloc, file="../output/SignalSitePlotbyLoc.png")

Saving 7 x 5 in image

Proportion:

allPAS_byloc=allPAS %>% separate(PAS,into=c("peakid", "loc"),sep="_") %>% group_by(loc) %>% summarise(nLoc=n())

allPAS_byloc_new=as.data.frame(allPAS_byloc$nLoc %>% t())
colnames(allPAS_byloc_new) = allPAS_byloc$loc



AllsiteDF_1per_sep_INTRON=AllsiteDF_1per_sep %>% filter(Location=="intron") %>%  group_by(Site,NegCount) %>% summarise(CountperPos=n()) %>% mutate(TotCount=sum(CountperPos),prop=CountperPos/(allPAS_byloc_new$intron)) %>% mutate(Cononical=ifelse(Site=="AATAAA", "AATAAA", ifelse(Site=="ATTAAA", "AATTAA", "Other")))

ggplot(AllsiteDF_1per_sep_INTRON, aes(group=Cononical, x=NegCount,y=prop, fill=Cononical)) + geom_histogram(position="stack",bins=5, stat="identity" ) + labs(x="Distance from PAS", y="Propotion of Intron annotated Sites", title="Location of annotated signal sites \nfor Intronic PAS", caption = "Other: AAAAAA, AAAAAG, AATACA, AATAGA,AATATA, ACTAAA, AGTAAA,CATAAA, GATAAA,TATAAA") +  scale_fill_manual(values = getPalette(colourCount))+  theme(text = element_text(size=20, face="bold"),axis.text.x = element_text(size = 16), legend.position = "bottom", axis.text.y = element_text(size = 16),plot.title = element_text(size=22),plot.caption = element_text(hjust = 0,size=10))

Warning: Ignoring unknown parameters: binwidth, bins, pad

Version	Author	Date
96d85de	brimittleman	2019-07-07
9c1dd66	brimittleman	2019-06-13
ef7ddfe	brimittleman	2019-04-27
4eb21ab	brimittleman	2019-04-26

AllsiteDF_1per_sep_UTR=AllsiteDF_1per_sep %>% filter(Location=="utr3") %>%  group_by(Site,NegCount) %>% summarise(CountperPos=n()) %>% mutate(TotCount=sum(CountperPos),prop=CountperPos/(allPAS_byloc_new$intron)) %>% mutate(Cononical=ifelse(Site=="AATAAA", "AATAAA", ifelse(Site=="ATTAAA", "AATTAA", "Other")))

ggplot(AllsiteDF_1per_sep_UTR, aes(group=Cononical, x=NegCount,y=prop, fill=Cononical)) + geom_histogram(position="stack", stat="identity" ) + labs(x="Distance from PAS", y="Propotion of UTR annotated Sites", title="Location of annotated signal sites \nin UTR",caption = "Other: AAAAAA, AAAAAG, AATACA, AATAGA,AATATA, ACTAAA, AGTAAA,CATAAA, GATAAA,TATAAA") +  scale_fill_manual(values = getPalette(colourCount)) + theme(text = element_text(size=20, face="bold"),axis.text.x = element_text(size = 16), legend.position = "bottom", axis.text.y = element_text(size = 16),plot.title = element_text(size=22),plot.caption = element_text(hjust = 0,size=10))+ guides(fill=guide_legend(nrow=1,byrow=TRUE))

Warning: Ignoring unknown parameters: binwidth, bins, pad

Version	Author	Date
96d85de	brimittleman	2019-07-07

Propwith=c(nrow(AllsiteDF_1per_sep %>% filter(Location=="intron"))/allPAS_byloc_new$intron,nrow(AllsiteDF_1per_sep %>% filter(Location=="utr3"))/allPAS_byloc_new$utr3,nrow(AllsiteDF_1per_sep %>% filter(Location=="utr5"))/allPAS_byloc_new$utr5,nrow(AllsiteDF_1per_sep %>% filter(Location=="cds"))/allPAS_byloc_new$cds,nrow(AllsiteDF_1per_sep %>% filter(Location=="end"))/allPAS_byloc_new$end)
Locations=c("intron", "utr3", "utr5", "Coding", "Downstream")
propdf=as.data.frame(cbind(Location=Locations,Proportion=Propwith))
propdf$Proportion=as.numeric(as.character(propdf$Proportion))

all=ggplot(propdf,aes(x=Location, y=Proportion, fill=Location)) + geom_bar(stat="identity") + theme(axis.text.x = element_text(angle = 90, hjust = 1))

AllsiteDF_1per_sep_noncon=AllsiteDF_1per_sep %>% filter(Site != "AATAAA")

Propwithnotcon=c(nrow(AllsiteDF_1per_sep_noncon %>% filter(Location=="intron"))/allPAS_byloc_new$intron,nrow(AllsiteDF_1per_sep_noncon %>% filter(Location=="utr3"))/allPAS_byloc_new$utr3,nrow(AllsiteDF_1per_sep_noncon %>% filter(Location=="utr5"))/allPAS_byloc_new$utr5,nrow(AllsiteDF_1per_sep_noncon %>% filter(Location=="cds"))/allPAS_byloc_new$cds,nrow(AllsiteDF_1per_sep_noncon %>% filter(Location=="end"))/allPAS_byloc_new$end)
Locations=c("intron", "utr3", "utr5", "Coding", "Downstream")
propdf_noncon=as.data.frame(cbind(Location=Locations,Proportion=Propwithnotcon))
propdf_noncon$Proportion=as.numeric(as.character(propdf_noncon$Proportion))

non=ggplot(propdf_noncon,aes(x=Location, y=Proportion, fill=Location)) + geom_bar(stat="identity")+theme(axis.text.x = element_text(angle = 90, hjust = 1))
non

Version	Author	Date
96d85de	brimittleman	2019-07-07
9c1dd66	brimittleman	2019-06-13
ef7ddfe	brimittleman	2019-04-27
4eb21ab	brimittleman	2019-04-26

AllsiteDF_1per_sep_con=AllsiteDF_1per_sep %>% filter(Site == "AATAAA")

Propwithcon=c(nrow(AllsiteDF_1per_sep_con %>% filter(Location=="intron"))/allPAS_byloc_new$intron,nrow(AllsiteDF_1per_sep_con %>% filter(Location=="utr3"))/allPAS_byloc_new$utr3,nrow(AllsiteDF_1per_sep_con %>% filter(Location=="utr5"))/allPAS_byloc_new$utr5,nrow(AllsiteDF_1per_sep_con %>% filter(Location=="cds"))/allPAS_byloc_new$cds,nrow(AllsiteDF_1per_sep_con %>% filter(Location=="end"))/allPAS_byloc_new$end)
Locations=c("intron", "utr3", "utr5", "Coding", "Downstream")
propdf_con=as.data.frame(cbind(Location=Locations,Proportion=Propwithcon))
propdf_con$Proportion=as.numeric(as.character(propdf_con$Proportion))

con=ggplot(propdf_con,aes(x=Location, y=Proportion, fill=Location)) + geom_bar(stat="identity")+ theme(axis.text.x = element_text(angle = 90, hjust = 1))
con

Version	Author	Date
96d85de	brimittleman	2019-07-07
9c1dd66	brimittleman	2019-06-13
ef7ddfe	brimittleman	2019-04-27
4eb21ab	brimittleman	2019-04-26

plot_grid(all, con, non, labels=c("All PAS", "Cononical PAS", "Non-conical PAS"))

Version	Author	Date
96d85de	brimittleman	2019-07-07

Strong evidence PAS

For future analysis I want to have a set of PAS with evidence for a signal site. I want those signal sites upstream 10-50 basepairs.

AllsiteDF_1per_use= AllsiteDF_1per %>% filter(Distance2PAS>10, Distance2PAS<50) %>% separate(PAS,into=c("peakid", "loc"),sep="_") %>% separate(peakid,into=c("Peaknum", "gene"),sep=":") %>% mutate(PAS=paste("peak", Peaknum, sep="")) %>% dplyr::rename("UpstreamDist"=NegCount) %>%  select(PAS, gene, loc, Site, UpstreamDist)

ggplot(AllsiteDF_1per_use, aes(x=loc)) + geom_histogram(stat="count")

Warning: Ignoring unknown parameters: binwidth, bins, pad

Version	Author	Date
96d85de	brimittleman	2019-07-07

Write these out for

write.table(AllsiteDF_1per_use, file="../data/PAS/PASwSignalSite.txt", col.names = T, row.names = F, quote = F, sep="\t")

Plot color cononical vs non cononical:

AllsiteDF_1per_prop_col= AllsiteDF_1per_prop %>% mutate(Cononical=ifelse(Site=="AATAAA", "AATAAA", ifelse(Site=="ATTAAA", "AATTAA", "Other")))

dist2signalsiteplotprop=ggplot(AllsiteDF_1per_prop_col, aes(group=Cononical, x=NegCount,y=prop, fill=Cononical)) + geom_histogram(position="stack",bins=50,stat="identity" ) + labs(x="Distance from PAS", y="Proportion of annotated Sites", title="Location of annotated signal sites",fill=" ", caption = "Other: AAAAAA, AAAAAG, AATACA, AATAGA,AATATA, ACTAAA, AGTAAA,CATAAA, GATAAA,TATAAA") +   theme(text = element_text(size=20, face="bold"),axis.text.x = element_text(size = 16), legend.position = "bottom", axis.text.y = element_text(size = 16),plot.title = element_text(size=22),plot.caption = element_text(hjust = 0,size=10))+ guides(fill=guide_legend(nrow=1,byrow=TRUE))  +  scale_fill_manual(values = getPalette(colourCount))

Warning: Ignoring unknown parameters: binwidth, bins, pad

dist2signalsiteplotprop

Version	Author	Date
1a928ed	brimittleman	2019-07-17
16e4212	brimittleman	2019-07-17

#scale_fill_discrete(name="Site", labels=c("AATAAA","ATTAAA", "AAAAAA, AAAAAG, AATACA, AATAGA, AATATA, ACTAAA, AGTAAA,CATAAA, GATAAA,TATAAA")

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] cowplot_0.9.4      gplots_3.0.1       reshape2_1.4.3    
 [4] workflowr_1.4.0    RColorBrewer_1.1-2 forcats_0.3.0     
 [7] stringr_1.3.1      dplyr_0.8.0.1      purrr_0.3.2       
[10] readr_1.3.1        tidyr_0.8.3        tibble_2.1.1      
[13] ggplot2_3.1.1      tidyverse_1.2.1    seqLogo_1.48.0    

loaded via a namespace (and not attached):
 [1] gtools_3.8.1       tidyselect_0.2.5   haven_1.1.2       
 [4] lattice_0.20-38    colorspace_1.3-2   generics_0.0.2    
 [7] htmltools_0.3.6    stats4_3.5.1       yaml_2.2.0        
[10] rlang_0.4.0        pillar_1.3.1       glue_1.3.0        
[13] withr_2.1.2        modelr_0.1.2       readxl_1.1.0      
[16] plyr_1.8.4         munsell_0.5.0      gtable_0.2.0      
[19] cellranger_1.1.0   rvest_0.3.2        caTools_1.17.1.1  
[22] evaluate_0.12      labeling_0.3       knitr_1.20        
[25] highr_0.7          broom_0.5.1        Rcpp_1.0.0        
[28] KernSmooth_2.23-15 backports_1.1.2    scales_1.0.0      
[31] gdata_2.18.0       jsonlite_1.6       fs_1.3.1          
[34] hms_0.4.2          digest_0.6.18      stringi_1.2.4     
[37] rprojroot_1.3-2    bitops_1.0-6       cli_1.1.0         
[40] tools_3.5.1        magrittr_1.5       lazyeval_0.2.1    
[43] crayon_1.3.4       whisker_0.3-2      pkgconfig_2.0.2   
[46] xml2_1.2.0         lubridate_1.7.4    assertthat_0.2.0  
[49] rmarkdown_1.10     httr_1.3.1         rstudioapi_0.10   
[52] R6_2.3.0           nlme_3.1-137       git2r_0.25.2      
[55] compiler_3.5.1

Signal Site analysis

Briana Mittleman

4/23/2019

Strong evidence PAS

Plot color cononical vs non cononical: