Signal Site analysis

Last updated: 2019-06-13

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Knit directory: apaQTL/analysis/

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Unstaged changes:
    Modified:   analysis/DiffIsoAnalysis.Rmd
    Modified:   analysis/Readdistagainstfeatures.Rmd
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Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.

File	Version	Author	Date	Message
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
html	799dd25	brimittleman	2019-04-24	Build site.
html	ccebe33	brimittleman	2019-04-24	Build site.
Rmd	4febc15	brimittleman	2019-04-24	return to original SAF
html	627fc45	brimittleman	2019-04-24	Build site.
html	dd07ef7	brimittleman	2019-04-24	Build site.
Rmd	6dc25d8	brimittleman	2019-04-24	update after SAF bug
html	26058a5	brimittleman	2019-04-24	Build site.
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(tidyverse)

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

✔ ggplot2 3.1.1       ✔ purrr   0.3.2  
✔ tibble  2.1.1       ✔ dplyr   0.8.0.1
✔ tidyr   0.8.3       ✔ stringr 1.3.1  
✔ readr   1.3.1       ✔ forcats 0.3.0

── Conflicts ────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

library(workflowr)

This is workflowr version 1.3.0
Run ?workflowr for help getting started

library(reshape2)


Attaching package: 'reshape2'

The following object is masked from 'package:tidyr':

    smiths

library(gplots)


Attaching package: 'gplots'

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    lowess

library(cowplot)


Attaching package: 'cowplot'

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    ggsave

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

Signal Site analysis

Briana Mittleman

4/23/2019

Signal site and usage relationship