Last updated: 2019-06-13

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Knit directory: apaQTL/analysis/

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Unstaged changes:
    Modified:   analysis/DiffIsoAnalysis.Rmd
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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 27b11e3 brimittleman 2019-04-23 start signal site analysis

library(tidyverse)
── Attaching packages ─────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
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library(workflowr)
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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))
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
4eb21ab brimittleman 2019-04-26
dd07ef7 brimittleman 2019-04-24
12d1cb0 brimittleman 2019-04-23

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")
dist2signalsiteplot

Version Author Date
4eb21ab brimittleman 2019-04-26
799dd25 brimittleman 2019-04-24
dd07ef7 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")
Warning: Ignoring unknown parameters: binwidth, bins, pad
dist2signalsiteplotprop

Version Author Date
4eb21ab brimittleman 2019-04-26
799dd25 brimittleman 2019-04-24
dd07ef7 brimittleman 2019-04-24
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)

dist2signalsiteplot_byloc

Version Author Date
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))

ggplot(AllsiteDF_1per_sep_INTRON, aes(group=Site, x=NegCount,y=prop, fill=Site)) + 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") 
Warning: Ignoring unknown parameters: binwidth, bins, pad

Version Author Date
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))

ggplot(AllsiteDF_1per_sep_UTR, aes(group=Site, x=NegCount,y=prop, fill=Site)) + geom_histogram(position="stack", stat="identity" ) + labs(x="Distance from PAS", y="Propotion of UTR annotated Sites", title="Location of annotated signal sites in UTR") 
Warning: Ignoring unknown parameters: binwidth, bins, pad

Version Author Date
ef7ddfe brimittleman 2019-04-27
4eb21ab brimittleman 2019-04-26
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
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
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
ef7ddfe brimittleman 2019-04-27
4eb21ab brimittleman 2019-04-26

Signal site and usage relationship

Next plot: look at presence of signal site compared to PAS usage

I need to look at the mean usage and fraction it by if the peak has a signal site.


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] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] cowplot_0.9.4   gplots_3.0.1    reshape2_1.4.3  workflowr_1.3.0
 [5] forcats_0.3.0   stringr_1.3.1   dplyr_0.8.0.1   purrr_0.3.2    
 [9] readr_1.3.1     tidyr_0.8.3     tibble_2.1.1    ggplot2_3.1.1  
[13] tidyverse_1.2.1

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    yaml_2.2.0         rlang_0.3.1       
[10] pillar_1.3.1       glue_1.3.0         withr_2.1.2       
[13] modelr_0.1.2       readxl_1.1.0       plyr_1.8.4        
[16] munsell_0.5.0      gtable_0.2.0       cellranger_1.1.0  
[19] rvest_0.3.2        caTools_1.17.1.1   evaluate_0.12     
[22] labeling_0.3       knitr_1.20         broom_0.5.1       
[25] Rcpp_1.0.0         KernSmooth_2.23-15 scales_1.0.0      
[28] backports_1.1.2    gdata_2.18.0       jsonlite_1.6      
[31] fs_1.2.6           hms_0.4.2          digest_0.6.18     
[34] stringi_1.2.4      grid_3.5.1         rprojroot_1.3-2   
[37] cli_1.0.1          tools_3.5.1        bitops_1.0-6      
[40] magrittr_1.5       lazyeval_0.2.1     crayon_1.3.4      
[43] whisker_0.3-2      pkgconfig_2.0.2    xml2_1.2.0        
[46] lubridate_1.7.4    assertthat_0.2.0   rmarkdown_1.10    
[49] httr_1.3.1         rstudioapi_0.10    R6_2.3.0          
[52] nlme_3.1-137       git2r_0.25.2       compiler_3.5.1