normalized read count per group from edgeR
2
0
Entering edit mode
@manoharankumar01-9971
Last seen 5.6 years ago

Dear All,

I am using following code for my expression analysis from the edgeR package.

col_ordering = c(1,2,3,4,5,6)
rnaseqMatrix = data[,col_ordering]
rnaseqMatrix = round(rnaseqMatrix)
rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,]
conditions = factor(c(rep("Set1", 3), rep("Set2", 3)))

exp_study = DGEList(counts=rnaseqMatrix, group=conditions)
exp_study = calcNormFactors(exp_study)
exp_study = estimateCommonDisp(exp_study)
exp_study = estimateTagwiseDisp(exp_study)

et = exactTest(exp_study)

tTags = topTags(et,n=NULL)
write.table(tTags, file='mirna.Set1_vs_Set2.edgeR.DE_results', sep=' ', quote=F, row.names=T)

I would like to get the normalised value Per Group (ie. Set1 & Set2) which is used in the exactTest. How can I get that? In otherwords the data which is used to calculate logFC?.

Best Regards,

Manoharan

microrna edger • 1.2k views
2
Entering edit mode
Aaron Lun ★ 27k
@alun
Last seen 4 hours ago
The city by the bay

The simplest way would be to do something like this:

design <- model.matrix(~0 + conditions)
fit <- glmFit(exp_study, design)

... then the values of fit\$coefficients/log(2) represent the normalized average log-expression in each group. Subtracting one from the other should recover the log-fold change (this will not be sorted, though, so you'll have to run topTags with sort.by='none' for them to match up).

0
Entering edit mode
@manoharankumar01-9971
Last seen 5.6 years ago

Dear Aaron Lun,

Thank you very much.

Best Regards,

Manoharan