I read this post ( C: Compute Binned Gc-Normalized Read Counts From Bam File ) and I am wondering how can I remove GC content bias with Loess regression?
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written
by
fatima.m.zare •
1 answer
Get 300kb bin window:
bedtools makewindows -g hg38.chrom.size -w 300000 > hg38_300.bed
hg38.chrom.size like this:
chr13 114364328
chr18 80373285
chr21 46709983
Get gc content
bedtools nuc -fi hs38DH.fa -bed hg38_300.bed | cut -f 1-3,5 > 300.gc.bed
Get depth in each bin:
bedtools coverage -a hg38_300.bed -b S1901020.aln.bam > S1901020.counts
combine gc content and depth:
paste <(grep -v '#' 300.gc.bed) <(cut -f4 S1901020.counts)|sed '1i chr\tstart\tend\tGC\tRC' > nipt
Rscript
RC_DT<- read.table('nipt',sep='\t',head=TRUE)
gcCount.loess <- loess(RC~GC,data=RC_DT,control = loess.control(surface = "direct"),degree=2)
predictions1<- predict (gcCount.loess,RC_DT$GC)
resi <- RC_DT$RC-predictions1
RC_DT$RC <- resi
the corrected RC in RC_DT$RC, more help about loess can be got in help document in R.
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If you have an issue with GC-bias, why not use computeGCBias and correctGCBias from deepTools?
Actually I want write my own code. I want to know about the method that use loess output and do correction for read counts. but Thanks for your answer. I will look at them maybe I can find their methods.