Search
Question: GC content and length bias in RNA-seq data
0
gravatar for parvin.shariaty
7 months ago by
parvin.shariaty0 wrote:

hi

I have seven RNA-seq data in two groups( control,treat) that produced from two companies (controls=BGI,treats=novogen). I used NOISeq to quality control of count data, and the results recommended normalization for GC content and length. But I have studied some papers and have founded that GC content and length normalization in gene expression comparison between two groups introduced bias. So I would like to use normalization factors instead of size factors in DESeq2(as described in differential analysis of count data - the DESeq2 package).

>normFactors<-matrix(runif(nrow(dds)*ncol(dds),0.5,1.5),ncol=ncol(dds),nrow=nrow(dds),dimnames=list(1:nrow(dds),1:ncol(dds)))

>normFactors<- normFactors / exp(rowMeans(log(normFactors)))

>normalizationFactors(dds)<- normFactors

>sizeFactors(dds)<-normFactors

Is it a correct manner to normalization and introduce the normalization factors in DESeq2? 

Thank you for cooperation in advance.

Parvin

 

ADD COMMENTlink modified 7 months ago by Michael Love19k • written 7 months ago by parvin.shariaty0
0
gravatar for Michael Love
7 months ago by
Michael Love19k
United States
Michael Love19k wrote:

The last line does nothing, and can be skipped. The rest is correct. (Except the runif(), presumably there just for demonstration.)

BTW, to notify the developers of a post here, you can add the package name as a tag. This will trigger an email to the maintainer.

ADD COMMENTlink modified 7 months ago • written 7 months ago by Michael Love19k
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.2.0
Traffic: 198 users visited in the last hour