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.

data = read.table("mirna.readcout", header=T, row.names=1, com='')

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?.

Looking forward for your reply, Thank you very much for your time.


Best Regards,

Manoharan

microrna edger • 1.2k views
ADD COMMENT
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).

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

Dear Aaron Lun,

Thank you very much.

Best Regards,

Manoharan

ADD COMMENT

Login before adding your answer.

Traffic: 501 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6