Last updated: 2018-08-28

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Unstaged changes:
    Modified:   analysis/28ind.peak.explore.Rmd
    Modified:   analysis/cleanupdtseq.internalpriming.Rmd
    Modified:   analysis/dif.iso.usage.leafcutter.Rmd
    Modified:   analysis/explore.filters.Rmd
    Modified:   analysis/peak.cov.pipeline.Rmd
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    File Version Author Date Message
    Rmd fa818a1 brimittleman 2018-08-28 first processing figure

I will use this analysis to work on vizualising some of the processing steps of this analysis.

Peaks per gene

I want to create a figure similar to the one I created in https://brimittleman.github.io/comparative_threeprime/characterize.ortho.peaks.html. I will use the count distinct function from bedtools map. For this I am using the RefSeq mRNA annotations.

#!/bin/bash

#SBATCH --job-name=refseq_countdistinct
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=refseq_countdistinct.out
#SBATCH --error=refseq_countdistinct.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END



bedtools map -c 4 -s -o count_distinct -a /project2/gilad/briana/genome_anotation_data/ncbiRefSeq_sm_noChr.sort.mRNA.bed -b   > /project2/gilad/briana/threeprimeseq/data/peakPerRefseqGene/filtered_APApeaks_perRefseqGene.txt 

library(tidyverse)
── Attaching packages ──────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.0.0     ✔ purrr   0.2.5
✔ tibble  1.4.2     ✔ dplyr   0.7.6
✔ tidyr   0.8.1     ✔ stringr 1.3.1
✔ readr   1.1.1     ✔ forcats 0.3.0
── Conflicts ─────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
library(workflowr)
This is workflowr version 1.1.1
Run ?workflowr for help getting started
library(reshape2)

Attaching package: 'reshape2'
The following object is masked from 'package:tidyr':

    smiths
library(cowplot)

Attaching package: 'cowplot'
The following object is masked from 'package:ggplot2':

    ggsave
names=c("Chr", "Start", "End", "Name", "Score", "Strand", "numPeaks")
peakpergene=read.table("../data/peakPerRefSeqGene/filtered_APApeaks_perRefseqGene.txt", stringsAsFactors = F, header = F, col.names = names) %>% mutate(onePeak=ifelse(numPeaks==1, 1, 0 )) %>%  mutate(multPeaks=ifelse(numPeaks > 1, 1, 0 ))
genes1peak=sum(peakpergene$onePeak)/nrow(peakpergene) 
genesMultpeak=sum(peakpergene$multPeaks)/nrow(peakpergene)
genes0peak= 1- genes1peak - genesMultpeak

perPeak= c(round(genes0peak,digits = 3), round(genes1peak,digits = 3),round(genesMultpeak, digits = 3))
Category=c("Zero", "One", "Multiple")
perPeakdf=as.data.frame(cbind(Category,as.numeric(perPeak)))

Plot these proportions:

lab1=paste("Genes =", genes0peak*nrow(peakpergene), sep=" ")
lab2=paste("Genes =", sum(peakpergene$onePeak), sep=" ")
lab3=paste("Genes =", sum(peakpergene$multPeaks), sep=" ")

genepeakplot=ggplot(perPeakdf, aes(x="", y=perPeak, fill=Category)) + geom_bar(stat="identity")+ labs(title="Characterize genes by number of PAS", y="Proportion of Protein Coding gene", x="")+ scale_fill_brewer(palette="Paired") + coord_cartesian(ylim=c(0,1)) + annotate("text", x="", y= .35, label=lab1) + annotate("text", x="", y= .78, label=lab2) + annotate("text", x="", y= .92, label=lab3)
genepeakplot

Session information

sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] bindrcpp_0.2.2  cowplot_0.9.3   reshape2_1.4.3  workflowr_1.1.1
 [5] forcats_0.3.0   stringr_1.3.1   dplyr_0.7.6     purrr_0.2.5    
 [9] readr_1.1.1     tidyr_0.8.1     tibble_1.4.2    ggplot2_3.0.0  
[13] tidyverse_1.2.1

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.4   haven_1.1.2        lattice_0.20-35   
 [4] colorspace_1.3-2   htmltools_0.3.6    yaml_2.2.0        
 [7] rlang_0.2.2        R.oo_1.22.0        pillar_1.3.0      
[10] glue_1.3.0         withr_2.1.2        R.utils_2.7.0     
[13] RColorBrewer_1.1-2 modelr_0.1.2       readxl_1.1.0      
[16] bindr_0.1.1        plyr_1.8.4         munsell_0.5.0     
[19] gtable_0.2.0       cellranger_1.1.0   rvest_0.3.2       
[22] R.methodsS3_1.7.1  evaluate_0.11      labeling_0.3      
[25] knitr_1.20         broom_0.5.0        Rcpp_0.12.18      
[28] scales_1.0.0       backports_1.1.2    jsonlite_1.5      
[31] hms_0.4.2          digest_0.6.16      stringi_1.2.4     
[34] grid_3.5.1         rprojroot_1.3-2    cli_1.0.0         
[37] tools_3.5.1        magrittr_1.5       lazyeval_0.2.1    
[40] crayon_1.3.4       whisker_0.3-2      pkgconfig_2.0.2   
[43] xml2_1.2.0         lubridate_1.7.4    assertthat_0.2.0  
[46] rmarkdown_1.10     httr_1.3.1         rstudioapi_0.7    
[49] R6_2.2.2           nlme_3.1-137       git2r_0.23.0      
[52] compiler_3.5.1

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