Last updated: 2019-01-14
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File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 6bc9243 | Briana Mittleman | 2019-01-14 | evaluate clean reads, make new file for misprime filter |
In the previous analysis I looked at a mispriming approach. Now I am going to use these filtered reads to create new BAM files, BW files, coverage files, and finally a peak list. After, I will evaluate the differences in the peak lists.
Now I need to filter the sorted bed files based on these clean reads.
I can make an R script that uses filter join:
Infile1 is the sorted bed, Infile2 is cleaned bed, Filter on read name
I can sue the number_T/N as the identifer.
filterSortBedbyCleanedBed.R
#!/bin/rscripts
# usage: Rscirpt --vanilla filterSortBedbyCleanedBed.R identifier
#this script takes in the sorted bed file and the clean reads, it will clean the bed file
library(dplyr)
library(tidyr)
library(data.table)
args = commandArgs(trailingOnly=TRUE)
identifier=args[1]
sortBedName= paste("/project2/gilad/briana/threeprimeseq/data/bed_sort/YL-SP-", identifier, "-combined-sort.bed", sep="")
CleanName= paste("/project2/gilad/briana/threeprimeseq/data/nuc_10up_CleanReads/TenBaseUP.", identifier, ".CleanReads.bed", sep="")
outFile= paste("/project2/gilad/briana/threeprimeseq/data/bed_sort_CleanedMP/YL-SP-", identifier, "-combined-sort.clean.bed", sep="")
bedFile=fread(sortBedName, col.names = c("Chrom", "start", "end", "name", "score", "strand"))
cleanFile=fread(CleanName, col.names = c("Chrom", "start", "end", "name", "score", "strand"))
intersection=bedFile %>% semi_join(cleanFile, by="name")
fwrite(intersection, file=outFile,quote = F, col.names = F, row.names = F)
I need to call this in a bash script that gets just the identifier:
run_filterSortBedbyCleanedBed.sh
#!/bin/bash
#SBATCH --job-name=run_filterSortBedbyCleanedBed
#SBATCH --account=pi-yangili1
#SBATCH --time=8:00:00
#SBATCH --output=run_filterSortBedbyCleanedBed.out
#SBATCH --error=run_filterSortBedbyCleanedBed.err
#SBATCH --partition=broadwl
#SBATCH --mem=36G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
for i in $(ls /project2/gilad/briana/threeprimeseq/data/nuc_10up_CleanReads/*);do
describer=$(echo ${i} | sed -e 's/.*TenBaseUP.//' | sed -e "s/.CleanReads.bed//")
Rscript --vanilla filterSortBedbyCleanedBed.R ${describer}
done
Next I can use bedtools intersect to filter the bam files from these bed files. I will write the code then wrap it.
filterOnlyOKPrimeFromBam.sh
a is the bam, b is the clean bed , stranded, sorted, -wa
#!/bin/bash
#SBATCH --job-name=filterOnlyOKPrimeFromBam
#SBATCH --account=pi-yangili1
#SBATCH --time=8:00:00
#SBATCH --output=filterOnlyOKPrimeFromBam.out
#SBATCH --error=filterOnlyOKPrimeFromBam.err
#SBATCH --partition=broadwl
#SBATCH --mem=36G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
$1 = describer
bedtools intersect -wa -sorted -s -abam /project2/gilad/briana/threeprimeseq/data/sort/YL-SP-${desciber}-combined-sort.bam -b /project2/gilad/briana/threeprimeseq/data/bed_sort_CleanedMP/YL-SP-${descirber}-combined-sort.clean.bed > /project2/gilad/briana/threeprimeseq/data/bam_NoMP/YL-SP-${desciber}-combined-sort.noMP.bam
I will sort and index these:
/project2/gilad/briana/threeprimeseq/data/sort_NoMP/
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
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