I'm carrying out DEA on a multifactorial design with 4 factors (sex (m/f), method (A/B), cat_group (AA/BB) and month(J/F/M) with cat_group being the focus of the contrast and and used last in the design
dds <- DESeqDataSetFromMatrix(countData = countsall,
colData = coldata,
design = ~ sex+month+method+cat)
I've used the default wald test and am applying ashr for LFCshrink which I think is the correct method, however I have previously used IHW for multiple testing correction, but it gives me an error message when I try and run this as filterFun when also running ahsr for shrinking values - is there a way of using both please? Or what is used for multiple testing correction otherwise when running with ashr?
IHW and ashr don't really mix. IHW is for adjustment of p-values -- which you would get from results(dds), whereas ashr is a Bayesian method for shrinking effect sizes and providing s-values. s-values are like adjusted p-values but provide a bound on the probability of wrong sign among the thresholded set.
What I've done before with scientists that prefer FDR sets (e.g. DESeq -> results with IHW), is to just compute the posterior fold changes for all genes and provide that as an additional column. These are still useful for ranking and visualization, even if you don't use the s-values to define the set of interest.