Last updated: 2018-12-11

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Unstaged changes:
    Modified:   analysis/28ind.peak.explore.Rmd
    Modified:   analysis/QTLsbyPCnum.Rmd
    Modified:   analysis/apaQTLoverlapGWAS.Rmd
    Modified:   analysis/cleanupdtseq.internalpriming.Rmd
    Modified:   analysis/coloc_apaQTLs_protQTLs.Rmd
    Modified:   analysis/dif.iso.usage.leafcutter.Rmd
    Modified:   analysis/diff_iso_pipeline.Rmd
    Modified:   analysis/explainpQTLs.Rmd
    Modified:   analysis/explore.filters.Rmd
    Modified:   analysis/flash2mash.Rmd
    Modified:   analysis/overlapMolQTL.Rmd
    Modified:   analysis/overlap_qtls.Rmd
    Modified:   analysis/peakOverlap_oppstrand.Rmd
    Modified:   analysis/pheno.leaf.comb.Rmd
    Modified:   analysis/swarmPlots_QTLs.Rmd
    Modified:   analysis/test.max2.Rmd
    Modified:   code/Snakefile
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In looking at correlations and some examples, there is evidence the peak to gene assignment may be a problem. I am going to visualize the peaks in IGV. I will name them by the gene and look at them in the browser.

The peak to gene annotations used in the feature counts to map reads back to the peaks is the following:
* /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed.bed

I need to change this a bit to have the name be the gene rather than the score:

NamePeaksByGene.py

#python  

CovnamedPeaks=open("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed.bed", "r")
GeneNamedPeaks=open("/project2/gilad/briana/threeprimeseq/data/UnderstandPeaksQC/PeaksNamedWithGeneAssignment.bed", "w")

for ln in CovnamedPeaks:
  chrom, start, end, num, cov, strand, transcript = ln.split()
  gene=transcript.split("-")[1]
  GeneNamedPeaks.write("%s\t%s\t%s\t%s\n"%(chrom,start,end,gene))

GeneNamedPeaks.close()

This was made based on the transcript annotation: ncbiRefSeq.mRNA.named.bed

  • /project2/gilad/briana/genome_anotation_data/ncbiRefSeq.mRNA.named.bed

The ends of the transcripts specfically are in:

  • /project2/gilad/briana/genome_anotation_data/ncbiRefSeq_endProtCodGenes_sort.txt

Ideas for Dilters:

  • Cant be upstream of the gene, ex: chr2:135,558,075-135,604,343

  • maybe it cant be in another gene

  • we should include LINCs

  • looks like we have a ton of low expressed intergenic peaks that should be filtered before we do the gene annotation

Filter out intergenic peaks

As a first pass I want to filter out the peaks that are outside a gene body. While this may not be perfect it will help alot with the intergenic noise.

I need to overlap the named peaks with /project2/gilad/briana/genome_anotation_data/ncbiRefSeq.mRNA.named.bed and only keep the matches. I can use bedtools intersect.

Rename the peaks according to convention to run an intesect.

RenamePeaks4Intersect.py

#python  
CovnamedPeaks=open("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed.bed", "r")
GeneNamedPeaks=open("/project2/gilad/briana/threeprimeseq/data/UnderstandPeaksQC/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_RENAMED.bed", "w")  

for ln in CovnamedPeaks:
  chrom, start, end, num, cov, strand, transcript = ln.split()
  gene=transcript.split("-")[1]
  start=int(start)
  end=int(end)
  GeneNamedPeaks.write("%s\t%d\t%d\t%s-%s\t%s\t%s\n"%(chrom,start,end,num,gene,cov,strand))

GeneNamedPeaks.close()

Remove CHR from the refseq annpotation:

sed 's/^chr//' /project2/gilad/briana/genome_anotation_data/ncbiRefSeq.mRNA.named.bed > /project2/gilad/briana/genome_anotation_data/ncbiRefSeq.mRNA.named_noCHR.bed

Filter4GenicPeaks.sh


#!/bin/bash


#SBATCH --job-name=Filter4GenicPeaks
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=Filter4GenicPeaks.out
#SBATCH --error=Filter4GenicPeaks.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END

module load Anaconda3
source activate three-prime-env


bedtools intersect -wa -s -a /project2/gilad/briana/threeprimeseq/data/UnderstandPeaksQC/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_RENAMED.bed -b /project2/gilad/briana/genome_anotation_data/ncbiRefSeq.mRNA.named_noCHR.bed > /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb_inGeneBody/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_inGeneBodies.bed

This is printing them multiple times.

uniq /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb_inGeneBody/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_inGeneBodies.bed > /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb_inGeneBody/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_inGeneBodiesUNIQ.bed

Now I need to make this an SAF to run feature counts.

bed2saf_peaksInGenicReg.py

from misc_helper import *

fout = open("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb_inGeneBody/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_inGeneBodiesUNIQ.SAF",'w')
fout.write("GeneID\tChr\tStart\tEnd\tStrand\n")
for ln in open("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb_inGeneBody/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_inGeneBodiesUNIQ.bed"):
    chrom, start, end, name, score, strand = ln.split()
    namenum=name.split("-")[0]
    name_i=int(namenum)
    start_i=int(start)
    end_i=int(end)
    gene_only=name.split("-")[1]
    ID = "peak%d:%s:%d:%d:%s:%s"%(name_i, chrom, start_i, end_i, strand, gene_only)
    fout.write("%s\t%s\t%d\t%d\t%s\n"%(ID, chrom, start_i, end_i, strand))
fout.close()

Run Feature Counts
PeaksinGenicRegion_fc_TN.sh

#!/bin/bash

#SBATCH --job-name=PeaksinGenicRegion_fc_TN
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=PeaksinGenicRegion_fc_TN.out
#SBATCH --error=PeaksinGenicRegion_fc_TN.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_comb_inGeneBody/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_inGeneBodiesUNIQ.SAF -F SAF -o /project2/gilad/briana/threeprimeseq/data/PeakInGenecRegion_cov/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_Genic.Total.fc /project2/gilad/briana/threeprimeseq/data/sort/*-T-*-sort.bam -s 2

featureCounts -O -a /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb_inGeneBody/filtered_APApeaks_merged_allchrom_refseqTrans.noties_sm.fixed_inGeneBodiesUNIQ.SAF -F SAF -o /project2/gilad/briana/threeprimeseq/data/PeakInGenecRegion_cov/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_Genic.Nuclear.fc /project2/gilad/briana/threeprimeseq/data/sort/*-N-*-sort.bam -s 2

Lastly I will need to fix the headers.

fix_head_fc_genicPeak_tot.py

infile= open("/project2/gilad/briana/threeprimeseq/data/PeakInGenecRegion_cov/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_Genic.Total.fc", "r")
fout = file("/project2/gilad/briana/threeprimeseq/data/PeakInGenecRegion_cov/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_Genic.Total_fixed.fc",'w')
for line, i in enumerate(infile):
    if line == 1:
        i_list=i.split()
        libraries=i_list[:6]
        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()

fix_head_fc_genicPeak_nuc.py

infile= open("/project2/gilad/briana/threeprimeseq/data/PeakInGenecRegion_cov/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_Genic.Nuclear.fc", "r")
fout = file("/project2/gilad/briana/threeprimeseq/data/PeakInGenecRegion_cov/filtered_APApeaks_merged_allchrom_refseqGenes.Transcript_sm_quant_Genic.Nuclear_fixed.fc",'w')
for line, i in enumerate(infile):
    if line == 1:
        i_list=i.split()
        libraries=i_list[:6]
        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()

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     

loaded via a namespace (and not attached):
 [1] workflowr_1.1.1   Rcpp_0.12.19      digest_0.6.17    
 [4] rprojroot_1.3-2   R.methodsS3_1.7.1 backports_1.1.2  
 [7] git2r_0.23.0      magrittr_1.5      evaluate_0.11    
[10] stringi_1.2.4     whisker_0.3-2     R.oo_1.22.0      
[13] R.utils_2.7.0     rmarkdown_1.10    tools_3.5.1      
[16] stringr_1.3.1     yaml_2.2.0        compiler_3.5.1   
[19] htmltools_0.3.6   knitr_1.20

This reproducible R Markdown analysis was created with workflowr 1.1.1