Hi,

I want to use mfuzz for clustering of RNA-seq results.

The problem is that I can't find easy solution how to average biological replicates. I assumed there is simple function for averaging replicates by conditions using info from phenoData for ExpressionSet or sample info in case of DESeqDataSet.

I use DESeq2 so I have DESeqDataSet object. I've prepared ExpressionSet object with standardised FPKM values for mfuzz but I've realised that I need to average value for each condition.

I know, I could use aggregate to average data in data frame but it is prone to error if used for object with many columns.

Many ways to do that, here are two:

library(DESeq2)
library(limma)

set.seed(1)
dds <- makeExampleDESeqDataSet()
ntf <- normTransform(dds)

# base R, assuming condition is a factor
rs <- rowsum(t(assay(ntf)), group = dds$condition)
rn <- as.numeric(table(ntf$condition))
averaged <- t(rs/rn)

# limma with transpose
averaged <- t(avereps(t(assay(ntf)), ID = ntf$condition))