edgeR VS deseq normalization

narges · 07-04-2013, 06:27 AM

Hi,

I intend to run RNA-seq analysis using DESeq package. But since I am working on TMM normalization method I wanted to run DESeq with TMM as well. I wanted to ask if it is enough if I pass the "norm.factors" obtained from "calcNormFactors" from edgeR to "sizeFactor" of DESeq. Or I should multiply the "norm.factors" by library size and then passed it to DESeq?
Or do you think it is meaningful or not?
So either of these:

Code:

normFactor <- calcNormFactors(countTable)
scale <- countTable$samples$lib.size*countTable$samples$norm.factors
cds <- newCountDataSet(countTable, conditions)
pData(cds)$sizeFactor <- scale

OR:

Code:

normFactor <- calcNormFactors(countTable)
cds <- newCountDataSet(countTable, conditions)
pData(cds)$sizeFactor <- normFactor

Thanks in advance

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07-04-2013, 06:27 AM	#1
narges Member Location: Finland Join Date: Aug 2012 Posts: 29	edgeR VS deseq normalization Hi, I intend to run RNA-seq analysis using DESeq package. But since I am working on TMM normalization method I wanted to run DESeq with TMM as well. I wanted to ask if it is enough if I pass the "norm.factors" obtained from "calcNormFactors" from edgeR to "sizeFactor" of DESeq. Or I should multiply the "norm.factors" by library size and then passed it to DESeq? Or do you think it is meaningful or not? So either of these: Code: normFactor <- calcNormFactors(countTable) scale <- countTable$samples$lib.size*countTable$samples$norm.factors cds <- newCountDataSet(countTable, conditions) pData(cds)$sizeFactor <- scale OR: Code: normFactor <- calcNormFactors(countTable) cds <- newCountDataSet(countTable, conditions) pData(cds)$sizeFactor <- normFactor Thanks in advance