Re: zero rna-seq values AFTER normalisation in edgeR

Hi Nick,



On Fri, Aug 15, 2014 at 9:23 AM, Nick N <[email protected]> wrote:

> I am using edgeR to analyze RNA-Seq data. This is my script:
>
>
> library("edgeR")
> #############################
> #read in metadata & DGE
> #############################
> composite_samples <- read.csv(file="samples.csv",header=TRUE,sep=",")
> counts <- readDGE(composite_samples$CountFiles)$counts
> #############################
> #Filter & Library Size Re-set
> #############################
> noint <- rownames(counts) %in% (c("no_feature", "ambiguous",
> "too_low_aQual", "not_aligned", "alignment_not_unique"))
> cpms <- cpm(counts)
> keep <- rowSums(cpms>1)>=3 & !noint
> counts <- counts[keep,]
> colnames(counts) <- composite_samples$SampleName
> d <- DGEList(counts=counts, group=composite_samples$Condition)
> d$samples$lib.size <- colSums(d$counts)
> #############################
> #Normalisation
> #############################
> d <- calcNormFactors(d)
> #############################
> #Recording the normalized counts
> #############################
> all_cpm=cpm(d, normalized.lib.size=TRUE)
> all_counts <- cbind(rownames(all_cpm), all_cpm)
> colnames(all_counts)[1] <- "Ensembl.Gene.ID"
> rownames(all_counts) <- NULL
> #############################
> #Estimate Dispersion
> #############################
> d <- estimateCommonDisp(d)
> d <- estimateTagwiseDisp(d)
> #############################
> #Perform a test
> #############################
> de_ctl_mo_composite <- exactTest(d, pair=c("NY", "N"))
>
>
> I believe that the variable "all_counts" shall contain the normalized
> counts for each sample in each condition.


This is a misunderstanding. The counts are not affected by the
normalization. Instead, the only thing that is affected is the norm.factors
column in the 'sample' list item of your DGEList. This is clearly explained
in the edgeR User's guide, on p. 12, under section 2.6.6.

Best,

Jim



My understanding is also that
> edgeR adds pseudocounts BEFORE performing the library normalisation. Thus
> it is possible that some values revert to being zero after normalisation.
> But I thought that this would happen rarely. Yet in a recent dataset I find
> an improbably large number of zero values in "all_counts" which made me
> think that my understanding of how pseudocounts and normalisation work in
> edgeR might be incorrect. Can, please, somebody comment on this?
>
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>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099

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