Compare new and old peaks

Last updated: 2019-04-30

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File	Version	Author	Date	Message
Rmd	eb0bd95	brimittleman	2019-04-30	add write out step
html	ac656aa	brimittleman	2019-04-30	Build site.
Rmd	f9b8195	brimittleman	2019-04-30	understand usage of new pas

library(tidyverse)

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

✔ ggplot2 3.1.0       ✔ 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

These results have 30k more PAS than the previous runs. I also see a confusing shift in mean usage for all of the PAS. I want to compare the distribution of usage for different sets of individuals to see if there is something inherently different about the 15 new individuals.

New vs old peaks

I want to compare the usage of the new peaks compared to the overall mean usage. To do this I need to seperate the new and old PAS.

newPAS5perc=read.table("../data/PAS/APAPAS_GeneLocAnno.5perc.bed", stringsAsFactors = F, col.names = c("chr", "start","end", "ID", "score", "strand"))
oldPAS5perc=read.table("../../threeprimeseq/data/peaks4DT/APAPAS_5percCov_fixedStrand.bed", stringsAsFactors = F, col.names = c("chr", "start", "end", "ID", "score", "strand"))

uniqnew=newPAS5perc %>% semi_join(oldPAS5perc, by=c("chr", "start", "end"))

Pull in the usage of the peaks:

Total

totalPeakUs=read.table("../data/phenotype/APApeak_Phenotype_GeneLocAnno.Total.fc", header = T, stringsAsFactors = F) %>% separate(chrom, sep = ":", into = c("chr", "start", "end", "id")) %>% separate(id, sep="_", into=c("gene", "loc", "strand", "peak"))

Warning: Expected 4 pieces. Additional pieces discarded in 4 rows [14735,
14736, 14737, 14738].

ind=colnames(totalPeakUs)[8:dim(totalPeakUs)[2]]
totalPeakUs_CountNum=read.table("../data/phenotype/APApeak_Phenotype_GeneLocAnno.Total.CountsOnlyNumeric", col.names = ind)


#numeric with anno
totalPeak=as.data.frame(cbind(totalPeakUs[,1:7], totalPeakUs_CountNum))

totalPeakUs_CountNum_mean=rowMeans(totalPeakUs_CountNum)

#append mean to anno
TotalPeakUSMean=as.data.frame(cbind(totalPeakUs[,1:7],mean=totalPeakUs_CountNum_mean))

uniqnewPasnum=uniqnew  %>% separate(ID ,into=c("peaknum", "geneloc"),sep=":") %>% mutate(peak=paste("peak", peaknum, sep="")) %>% select(peak)

Filter these inthe mean usage:

TotalPeakUSMeanClass= TotalPeakUSMean %>% mutate(New=ifelse(peak %in% uniqnewPasnum$peak,"new", "original")) %>% mutate(Cutoff=ifelse(mean>=.05, "Yes", "No"))

mean(TotalPeakUSMean$mean)

[1] 0.2378282

Plot:

ggplot(TotalPeakUSMeanClass, aes(y=mean,x=New)) + geom_violin() + geom_hline(yintercept = mean(TotalPeakUSMean$mean), col="red") + facet_grid(~Cutoff)

Version	Author	Date
ac656aa	brimittleman	2019-04-30

This shows me the new peaks are not the peaks that barely passed the cuttoff before. These peaks cover the distribution of usage.

write out file with information about new and old peaks

Peak_newOld=TotalPeakUSMeanClass %>% select(-mean)
write.table(Peak_newOld, file="../data/peaks_5perc/NewVOldPeaks.txt", col.names = T, row.names = F, quote=F)

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

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[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
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 [5] purrr_0.3.2     readr_1.3.1     tidyr_0.8.3     tibble_2.1.1   
 [9] ggplot2_3.1.0   tidyverse_1.2.1

loaded via a namespace (and not attached):
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[41] htmltools_0.3.6  rvest_0.3.2      assertthat_0.2.0 colorspace_1.3-2
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[49] broom_0.5.1      crayon_1.3.4

Compare new and old peaks

Briana Mittleman

4/30/2019

New vs old peaks

Total