Sample filter after min_prevalence

Hi, I am using MaAsLin2 which is a great tool. One sample question: after filtering the features based on min_prevalence and min_abundance as set, in same cases, some samples will have no any features left, how does MaAsLin2 deal with these samples, remove or keep them for subsequent analysis?

MaAsLin2 doesn’t do any explicit checks for “seemingly empty” samples like you describe, so they will be kept among the inputs to the downstream modeling step.