Thanks a lot, sir for suggesting the book. I have noticed one thing when analyzed HUMAnN output data with MaAsLin2 and Lefse. After Lefse, I got around 30 significant features (P<0.05, without FDR correction). But, in MaAsLin2 output I’m getting no significant features because, the lowest q-value among all the features is 0.4 (default q-value <0.25). But, if I filter the features with P-value <0.05 from the MaAsLin2 output, I see, most of them are the same as that of Lefse output.
In this context, I am totally confused about whether I should consider those outputs from Lefse and report or not. One post in biobakery forum states adjustment is not necessary for Lefse (although @sma emphasised on “personal preferences” ). I also suspect if P-value adjustment is discarding the true significant features.
Please, suggest me what should I do.