I'm using metagneomeSeq to analyze data.
After creating MRexperiment, I had 31 features within 87 samples.
However, after using sparsefeature > 0) < 10), there was 0 feature left, which was weird, because none of the rows actually had sum of counts less than 10 in the original MRexperiment.
> sparseFeatures = which(rowSums(MRcounts(Phylum) > 0) < 10)
> Phylumtrim = Phylum[-sparseFeatures, ]
MRexperiment (storageMode: environment)
assayData: 0 features, 87 samples
element names: counts
When I use cumNormStat, I received a warning about "empty samples", but all of my samples had at least 1 feature that had counts over 10.
Phylumnorm = cumNorm(Phylumtrim,p= cumNormStat(Phylumtrim))
Error in cumNormStat(Phylumtrim) : Warning empty sample
How should I fix this problem? Or should I just skip sparsefeature?