I want to remove samples with missing phenotypes from the matrix, and to do so I use
mt = mt.filter_cols(~hl.is_nan(mt.pheno))
It appears to indeed exclude samples, but if I test the opposite, keeping the samples with a missing phenotype,
mt = mt.filter_cols(hl.is_nan(mt.pheno)), I get 0 when I count the columns, so I’m worried it’s not working the way I think it is and that the exclusion I see does not truly correspond to what I intend to do.
Could anyone explain it to me please?