Hello. I am using metagenomeSeq for a metagenomic dataset. We are assessing relative abundance of specific genes. These genes belong to different classes and mechanisms, and therefore we want to conduct this analysis at multiple levels to compare results (much like one would do analysis at species, genus, family levels). I am using metagenomeSeq's function "aggTax" to aggregate:
AggObj = aggTax(MRcounts(obj, norm=TRUE, log=FALSE),norm=TRUE, log=FALSE, lvl = Class, out = "MRexperiment")
As you can see, I am using the normalized counts for aggregation, as I believe it is standard procedure to normalize at the lowest level. After I've done this, I need to re-populate the normFactors slot, but I'm not sure what I should re-populate it with, as the libSize values are now the aggregated, normalized counts. I realize that the normFactors slot is necessary to run fitZig (as a related aside, I am running it with option useCSSoffset=FALSE). I tried setting p=0 and running cumNorm, but this still resulted in small values populating the normFactors slot, which I don't understand -- does this have something to do with accounting for different processes for creating 0 counts?
I'm not sure where to go from here, and any help would be greatly appreciated!