Good afternoon,
A while ago I asked how to treat 3 samples per individual (ID) in a DESEQ2. It was recommended to use Duplicate Correlation in limma. I wonder how to combine both packages:
I run my DESEQ2 with
dds0 <- DESeqDataSetFromMatrix(countData = cts,
colData = colData,
design = ~ AGE+ DIAGNOSIS + SEX)
I see that the duplicate correlation is run with
dupcor <- duplicateCorrelation(vobj, design, block=colData$ID)
(https://rdrr.io/bioc/limma/man/dupcor.html).
I struggle to combine both approaches here. Can give me a hint?
Unfortunately, I cannot find any example code online of someone using both approaches together.
Thanks so much, Bine
Ok thank you. Do you know by any chance if there is now an option to do this in DESEQ2? Someone told me recently that I could use ID as a block, I cant find anything of it, been searching for a while now.
This was asked many times before, the developer has suggested to use limma for these types of analysis: DESeq2 handling of replicates
Yes, i know it was asked many times before. I thought maybe something was developed in the meantime since recently someone told me something as mentioned above. Thanks.
No, we don't have plans to support random effects / correlations _within_ condition group. Blocking across condition is of course covered by including fixed effects in the regression.