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@mortonjt,

I have a follow-up question. I saw on another post (Gneiss ols regression model fitting) that you recommended filtering the data by:

  1. Features that have few reads (i.e. less than 10 reads across all samples).
  2. Features that are rarely observed (i.e. present in less than 5 samples in a study).
  3. Features that have very low variance (i.e. less than 10e-4)

Could you please provide the command in QIIME2 to do that filtering?

I am assuming the filtering would have to be done in the first step. Before running any clustering analysis (that might have default pseudocount transformation) or before running something like “composition add-pseudocount”.

Thank you, Joao