Fraction Differences with Processed data

Last updated: 2019-01-22

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File	Version	Author	Date	Message
Rmd	fd184be	Briana Mittleman	2019-01-22	add code for leafcutter on processed

library(workflowr)

This is workflowr version 1.1.1
Run ?workflowr for help getting started

In this analysis https://brimittleman.github.io/threeprimeseq/PeakToGeneAssignment.html I ran an initial run of the leafcutter tool for differences between fractions. I will use the same pipeline here for the processed data.

This starts with running feature counts with all of the peaks. I will use peaks passing the filter in either the total or nucelar fraction. These peaks are in /project2/gilad/briana/threeprimeseq/data/mergedPeaks_noMP_filtered/Filtered_APApeaks_merged_allchrom_noMP.sort.named.noCHR.refseqTrans.closest2end.sm.fixed_5percCov.bed and were created using the filternamePeaks5percCov.py script. I need to make this into an SAF file for FC.

This file has chr, start, end, peakNu, cov, strand, transcript:gene, distance. For the SAF file I want GeneID, Chr, start, end, strand. The GeneID is peak#:chr:start:end:strand:gene

bed2saf_bothFrac_Processed.py

from misc_helper import *

fout = open("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_noMP_filtered/Filtered_APApeaks_merged_allchrom_noMP.sort.named.noCHR.refseqTrans.closest2end.sm.fixed_5percCov.SAF",'w')
fout.write("GeneID\tChr\tStart\tEnd\tStrand\n")
for ln in open("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_noMP_filtered/Filtered_APApeaks_merged_allchrom_noMP.sort.named.noCHR.refseqTrans.closest2end.sm.fixed_5percCov.bed"):
    chrom, start, end, peakNum, cov, strand, trans, dist = ln.split()
    gene=trans.split(":")[1]
    ID = "peak%s:%s:%s:%s:%s:%s"%(peakNum,chrom,start, end,strand,gene)
    fout.write("%s\t%s\t%s\t%s\t%s\n"%(ID, chrom, start, end, strand))
fout.close()

bothFrac_processed_FC.sh

#!/bin/bash

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

module load Anaconda3
source activate three-prime-env


featureCounts -O -a /project2/gilad/briana/threeprimeseq/data/mergedPeaks_noMP_filtered/Filtered_APApeaks_merged_allchrom_noMP.sort.named.noCHR.refseqTrans.closest2end.sm.fixed_5percCov.SAF -F SAF -o /project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov_processed_bothFrac/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed.fc /project2/gilad/briana/threeprimeseq/data/bam_NoMP_sort/*sort.bam -s 2

Fix headers:

fix_head_fc_procBothFrac.py


#python 

infile= open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov_processed_bothFrac/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed.fc", "r")
fout = open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov_processed_bothFrac/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed_fixed.fc",'w')
for line, i in enumerate(infile):
    if line == 1:
        i_list=i.split()
        libraries = i_list[:6]
        print(libraries)
        for sample in i_list[6:]:
            full = sample.split("/")[7]
            samp= full.split("-")[2:4]
            lim="_"
            samp_st=lim.join(samp)
            libraries.append(samp_st)
        first_line= "\t".join(libraries)
        fout.write(first_line + '\n')
    else :
        fout.write(i)
fout.close()

fc2leafphen_processed.py

inFile= open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov_processed_bothFrac/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed_fixed.fc", "r")
outFile= open("/project2/gilad/briana/threeprimeseq/data/pheno_DiffIso_processed/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed_forLC.fc", "w")

for num, ln in enumerate(inFile):
        if num == 1:
            lines=ln.split()[6:]
            outFile.write(" ".join(lines)+'\n')
        if num > 1:
            ID=ln.split()[0]
            peak=ID.split(":")[0]
            chrom=ID.split(":")[1]
            start=ID.split(":")[2]
            start=int(start)
            end=ID.split(":")[3]
            end=int(end)
            strand=ID.split(":")[4]
            gene=ID.split(":")[5]
            new_ID="chr%s:%d:%d:%s"%(chrom, start, end, gene)
            pheno=ln.split()[6:]
            pheno.insert(0, new_ID)
            outFile.write(" ".join(pheno)+'\n')
            
outFile.close()

subset_diffisopheno_processed.py

def main(inFile, outFile, target):
    ifile=open(inFile, "r")
    ofile=open(outFile, "w")
    target=int(target)
    for num, ln in enumerate(ifile):
        if num == 0:
            ofile.write(ln)
        else:
            ID=ln.split()[0]
            chrom=ID.split(":")[0][3:]
            print(chrom)
            chrom=int(chrom)
            if chrom == target:
                ofile.write(ln)
            
if __name__ == "__main__":
    import sys

    target = sys.argv[1]
    inFile = "/project2/gilad/briana/threeprimeseq/data/pheno_DiffIso_processed/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed_forLC.fc"
    outFile = "/project2/gilad/briana/threeprimeseq/data/pheno_DiffIso_processed/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed_forLC_%s.txt"%(target)
    main(inFile, outFile, target)

Run this with: run_subset_diffisopheno_processed.sh

#!/bin/bash

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

module load Anaconda3
source activate three-prime-env

for i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 
do
python subset_diffisopheno_processed.py $i 
done

Make new sample list. I could use the old one but I want to have this pipeline work when I add individuals.

makeLCSampleList_processed.py

outfile=open("/project2/gilad/briana/threeprimeseq/data/pheno_DiffIso_processed/sample_groups.txt", "w")
infile=open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov_processed_bothFrac/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed.fc", "r")

for line, i in enumerate(infile):
    if line == 1:
        i_list=i.split()
        libraries=[]
        for sample in i_list[6:]:
            full = sample.split("/")[7]
            samp= full.split("-")[2:4]
            lim="_"
            samp_st=lim.join(samp)
            libraries.append(samp_st)
        for l in libraries:
            if l[-1] == "T":
                outfile.write("%s\tTotal\n"%(l))
            else:
                outfile.write("%s\tNuclear\n"%(l))
    else:
          next
                
outfile.close()

run_leafcutter_ds_bychrom_processed.sh

#!/bin/bash

#SBATCH --job-name=run_leafcutter_ds_bychrom_processed
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=run_leafcutter_ds_bychrom_processed.out
#SBATCH --error=run_leafcutter_ds_bychrom_processed.err
#SBATCH --partition=bigmem2
#SBATCH --mem=50G
#SBATCH --mail-type=END

module load R

for i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 
do
Rscript /project2/gilad/briana/davidaknowles-leafcutter-c3d9474/scripts/leafcutter_ds.R --num_threads 4  /project2/gilad/briana/threeprimeseq/data/pheno_DiffIso_processed/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_processed_forLC_${i}.txt /project2/gilad/briana/threeprimeseq/data/pheno_DiffIso_processed/sample_groups.txt -o /project2/gilad/briana/threeprimeseq/data/diff_iso_processed/TN_diff_isoform_chr${i}.txt 
done

Session information

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14.1

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] workflowr_1.1.1

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.19      digest_0.6.17     rprojroot_1.3-2  
 [4] R.methodsS3_1.7.1 backports_1.1.2   git2r_0.23.0     
 [7] magrittr_1.5      evaluate_0.11     stringi_1.2.4    
[10] whisker_0.3-2     R.oo_1.22.0       R.utils_2.7.0    
[13] rmarkdown_1.10    tools_3.5.1       stringr_1.3.1    
[16] yaml_2.2.0        compiler_3.5.1    htmltools_0.3.6  
[19] knitr_1.20

This reproducible R Markdown analysis was created with workflowr 1.1.1

Fraction Differences with Processed data

Briana Mittleman

1/22/2019

Session information