Last updated: 2018-08-30
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File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | ed1f658 | Briana Mittleman | 2018-08-30 | write code to rerun QTL with off strand |
In the dataprocfigures file I realized the peaks mapp to the opposite strand. I want to remap the peaks to genes on the opposite strand make the phenotpyes and rerun the QTL analysis.
#!/bin/bash
#SBATCH --job-name=intGenes_combfilterPeaksOppStrand
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=intGenes_combfilterPeaksOppStrand.out
#SBATCH --error=intGenes_combfilterPeaksOppStrand.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
bedtools intersect -wa -wb -sorted -S -a /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom.named.fixed.bed -b /project2/gilad/briana/genome_anotation_data/ncbiRefSeq_sm_noChr.sort.mRNA.bed > /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand.bed
Get rid of the extra columns. I will now use the gene strand so the feature counts can be stranded.
awk '{print $1 "\t" $2 "\t" $3 "\t" $4 "\t" $5 "\t" $12 "\t" $10}' /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand.bed > /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm.bed
Make this an SAF file with the correct peak ID. bed2saf_oppstrand_peaks.py
from misc_helper import *
fout = file("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm.SAF",'w')
fout.write("GeneID\tChr\tStart\tEnd\tStrand\n")
for ln in open("/project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm.bed"):
chrom, start, end, name, score, strand, gene = ln.split()
name_i=int(name)
start_i=int(start)
end_i=int(end)
ID = "peak%d:%s:%d:%d:%s:%s"%(name_i, chrom, start_i, end_i, strand, gene)
fout.write("%s\t%s\t%d\t%d\t%s\n"%(ID, chrom, start_i, end_i, strand))
fout.close()
Run feature counts:
ref_gene_peakOppStrand_fc.sh
#!/bin/bash
#SBATCH --job-name=ref_gene_peakOppStrand_fc
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=ref_gene_peakOppStrand_fc.out
#SBATCH --error=ref_gene_peakOppStrand_fc.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
featureCounts -a /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm.SAF -F SAF -o /project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.fc /project2/gilad/briana/threeprimeseq/data/sort/*-sort.bam -s 1
Also do this for total and nuclear seperately.
#!/bin/bash
#SBATCH --job-name=ref_gene_peakOppStrand_fc_TN
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=ref_gene_peakOppStrand_fc_TN.out
#SBATCH --error=ref_gene_peakOppStrand_fc_TN.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
featureCounts -a /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm.SAF -F SAF -o /project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.fc /project2/gilad/briana/threeprimeseq/data/sort/*-T-*-sort.bam -s 1
featureCounts -a /project2/gilad/briana/threeprimeseq/data/mergedPeaks_comb/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm.SAF -F SAF -o /project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.fc /project2/gilad/briana/threeprimeseq/data/sort/*-N-*-sort.bam -s 1
Fix the headers:
infile= open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.fc", "r")
fout = file("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.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()
infile= open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.fc", "r")
fout = file("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.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()
Create file IDS:
fout = file("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/file_id_mapping_total.txt",'w')
infile= open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total_fixed.fc", "r")
for line, i in enumerate(infile):
if line == 0:
i_list=i.split()
files= i_list[10:-2]
for each in files:
full = each.split("/")[7]
samp= full.split("-")[2:4]
lim="_"
samp_st=lim.join(samp)
outLine= full[:-1] + "\t" + samp_st
fout.write(outLine + "\n")
fout.close()
fout = file("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/file_id_mapping_nuclear.txt",'w')
infile= open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear_fixed.fc", "r")
for line, i in enumerate(infile):
if line == 0:
i_list=i.split()
files= i_list[10:-2]
for each in files:
full = each.split("/")[7]
samp= full.split("-")[2:4]
lim="_"
samp_st=lim.join(samp)
outLine= full[:-1] + "\t" + samp_st
fout.write(outLine + "\n")
fout.close()
Make Phenotypes:
#PYTHON 3
dic_IND = {}
dic_BAM = {}
for ln in open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/file_id_mapping_total.txt"):
bam, IND = ln.split()
IND = IND.strip()
dic_IND[bam] = IND
if IND not in dic_BAM:
dic_BAM[IND] = []
dic_BAM[IND].append(bam)
#now I have ind dic with keys as the bam and ind as the values
#I also have a bam dic with ind as the keys and bam as the values
inds=list(dic_BAM.keys()) #list of ind libraries
#list of genes
count_file=open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total_fixed.fc", "r")
genes=[]
for line , i in enumerate(count_file):
if line > 1:
i_list=i.split()
id=i_list[0]
id_list=id.split(":")
gene=id_list[5]
if gene not in genes:
genes.append(gene)
#make the ind and gene dic
dic_dub={}
for g in genes:
dic_dub[g]={}
for i in inds:
dic_dub[g][i]=0
#populate the dictionary
count_file=open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total_fixed.fc", "r")
for line, i in enumerate(count_file):
if line > 1:
i_list=i.split()
id=i_list[0]
id_list=id.split(":")
g= id_list[5]
values=list(i_list[6:])
list_list=[]
for ind,val in zip(inds, values):
list_list.append([ind, val])
for num, name in enumerate(list_list):
dic_dub[g][list_list[num][0]] += int(list_list[num][1])
#write the file by acessing the dictionary and putting values in the table ver the value in the dic
fout=open("/project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt","w")
peak=["PeakID"]
fout.write(" ".join(peak + inds) + '\n' )
count_file=open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total_fixed.fc", "r")
for line , i in enumerate(count_file):
if line > 1:
i_list=i.split()
id=i_list[0]
id_list=id.split(":")
gene=id_list[5]
buff=[id]
for x,y in zip(i_list[6:], inds):
b=int(dic_dub[gene][y])
t=int(x)
buff.append("%d/%d"%(t,b))
fout.write(" ".join(buff)+ '\n')
fout.close()
#PYTHON 3
dic_IND = {}
dic_BAM = {}
for ln in open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/file_id_mapping_nuclear.txt"):
bam, IND = ln.split()
IND = IND.strip()
dic_IND[bam] = IND
if IND not in dic_BAM:
dic_BAM[IND] = []
dic_BAM[IND].append(bam)
#now I have ind dic with keys as the bam and ind as the values
#I also have a bam dic with ind as the keys and bam as the values
inds=list(dic_BAM.keys()) #list of ind libraries
#list of genes
count_file=open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear_fixed.fc", "r")
genes=[]
for line , i in enumerate(count_file):
if line > 1:
i_list=i.split()
id=i_list[0]
id_list=id.split(":")
gene=id_list[5]
if gene not in genes:
genes.append(gene)
#make the ind and gene dic
dic_dub={}
for g in genes:
dic_dub[g]={}
for i in inds:
dic_dub[g][i]=0
#populate the dictionary
count_file=open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear_fixed.fc", "r")
for line, i in enumerate(count_file):
if line > 1:
i_list=i.split()
id=i_list[0]
id_list=id.split(":")
g= id_list[5]
values=list(i_list[6:])
list_list=[]
for ind,val in zip(inds, values):
list_list.append([ind, val])
for num, name in enumerate(list_list):
dic_dub[g][list_list[num][0]] += int(list_list[num][1])
#write the file by acessing the dictionary and putting values in the table ver the value in the dic
fout=open("/project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt","w")
peak=["PeakID"]
fout.write(" ".join(peak + inds) + '\n' )
count_file=open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear_fixed.fc", "r")
for line , i in enumerate(count_file):
if line > 1:
i_list=i.split()
id=i_list[0]
id_list=id.split(":")
gene=id_list[5]
buff=[id]
for x,y in zip(i_list[6:], inds):
b=int(dic_dub[gene][y])
t=int(x)
buff.append("%d/%d"%(t,b))
fout.write(" ".join(buff)+ '\n')
fout.close()
I can run these with the following bash script:
#!/bin/bash
#SBATCH --job-name=run_makepheno_sep
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=run_makepheno_sep.out
#SBATCH --error=run_makepheno_sep.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
python makePhenoRefSeqPeaks_opp_Total.py
python makePhenoRefSeqPeaks_opp_Nuclear.py
I will do this in the /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/ directory.
module load samtools
#zip file
gzip filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt
module load python
#leafcutter script
python /project2/gilad/briana/threeprimeseq/code/prepare_phenotype_table.py filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt.gz
#source activate three-prime-env
sh filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt_prepare.sh
#run for nuclear as well
gzip filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt
#unload anaconda, load python
python /project2/gilad/briana/threeprimeseq/code/prepare_phenotype_table.py filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt.gz
#load anaconda and env.
sh filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt.gz_prepare.sh
#filtered_APApeaks_merged_allchrom_refseqGenes_pheno_Total.txt.gz.PCs
#filtered_APApeaks_merged_allchrom_refseqGenes_pheno_Nuclear.txt.gz.PCs
Make a sample list.
#make a sample list
fout = file("/project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/SAMPLE.txt",'w')
for ln in open("/project2/gilad/briana/threeprimeseq/data/filtPeakOppstrand_cov/file_id_mapping_nuclear.txt"", "r"):
bam, sample = ln.split()
line=sample[:-2]
fout.write("NA"+line + "\n")
fout.close()
** Manually ** Remove 18500, 19092 and 19193, 18497
#!/bin/bash
#SBATCH --job-name=APAqtl_nominal_opp
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=APAqtl_nominal_opp.out
#SBATCH --error=APAqtl_nominal_opp.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
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
/home/brimittleman/software/bin/FastQTL/bin/fastQTL.static --vcf /project2/gilad/briana/YRI_geno_hg19/chr$i.dose.filt.vcf.gz --cov /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt.gz.2PCs --bed /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt.gz.qqnorm_chr$i.gz --out /project2/gilad/briana/threeprimeseq/data/nominal_APAqtl_Opp/filtered_APApeaks_merged_allchrom_refseqGenes_pheno_Nuclear.txt.gz.qqnorm_chr$i.nominal.out --chunk 1 1 --window 5e4 --include-samples /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/SAMPLE.txt
done
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
/home/brimittleman/software/bin/FastQTL/bin/fastQTL.static --vcf /project2/gilad/briana/YRI_geno_hg19/chr$i.dose.filt.vcf.gz --cov /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt.gz.2PCs --bed /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt.gz.qqnorm_chr$i.gz --out /project2/gilad/briana/threeprimeseq/data/nominal_APAqtl_Opp/filtered_APApeaks_merged_allchrom_refseqGenes_pheno_Total.txt.gz.qqnorm_chr$i.nominal.out --chunk 1 1 --window 5e4 --include-samples /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/SAMPLE.txt
done
#!/bin/bash
#SBATCH --job-name=APAqtl_perm_opp
#SBATCH --account=pi-yangili1
#SBATCH --time=24:00:00
#SBATCH --output=APAqtl_perm_opp.out
#SBATCH --error=APAqtl_perm_opp.err
#SBATCH --partition=broadwl
#SBATCH --mem=12G
#SBATCH --mail-type=END
for i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
do
/home/brimittleman/software/bin/FastQTL/bin/fastQTL.static --permute 1000 --vcf /project2/gilad/briana/YRI_geno_hg19/chr$i.dose.filt.vcf.gz --cov /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt.gz.2PCs --bed /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Nuclear.pheno_fixed.txt.gz.qqnorm_chr$i.gz --out /project2/gilad/briana/threeprimeseq/data/perm_APAqtl_Opp/filtered_APApeaks_merged_allchrom_refseqGenes_pheno_Nuclear.txt.gz.qqnorm_chr$i.perm.out --chunk 1 1 --window 5e4 --include-samples /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/SAMPLE.txt
done
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
/home/brimittleman/software/bin/FastQTL/bin/fastQTL.static --permute 1000 --vcf /project2/gilad/briana/YRI_geno_hg19/chr$i.dose.filt.vcf.gz --cov /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt.gz.2PCs --bed /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/filtered_APApeaks_merged_allchrom_refseqGenes.OppStrand_sm_quant.Total.pheno_fixed.txt.gz.qqnorm_chr$i.gz --out /project2/gilad/briana/threeprimeseq/data/perm_APAqtl_Opp/filtered_APApeaks_merged_allchrom_refseqGenes_pheno_Total.txt.gz.qqnorm_chr$i.perm.out --chunk 1 1 --window 5e4 --include-samples /project2/gilad/briana/threeprimeseq/data/phenotypes_filtPeakOppstrand/SAMPLE.txt
done
Run the normalversion if there are certain chromosome dont work. https://brimittleman.github.io/threeprimeseq/apaQTLwLeafcutter.html
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
loaded via a namespace (and not attached):
[1] workflowr_1.1.1 Rcpp_0.12.18 digest_0.6.16
[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