Some users (including myself) have noticed that in some cases ANCOM behaves oddly in that it identifies very low/0 W valued taxa as differentially abundant. See here and here for example of this behavior.
In contacting one of the developer’s of ANCOM regarding this issue ,Dr. Peddada had the following explanation/recommendation.
A potential reason for the problem is that the earlier code was trying to empirically derive the threshold for significance. When W takes on small values across almost all
samplestaxa, the threshold calculation does not work well. For this reason, we have modified the threshold calculation by providing fixed thresholds (.6, .7, .8). We typically recommend .7 (all our simulations are based on .7). The user can see how different the results between .6, .7, .8 (which are printed side by side). Higher the threshold the more conservative ANCOM would become and lower the threshold the more aggressive ANCOM would become. Unless your data are very peculiar, the results would be different but not dramatically different.
Of course, the above update refers to ANCOM2 which is currently available as an R code
only and does not reflect the current q2-ancom plugin. Though, I am told an updated q2 adaptation is in the works, so stay tuned for that.
In the meantime, please be wiry that in these situations with very low/zero W values the taxa are actually not significant.
ANCOM2 can also handle covariates and longitudinal data which are extremely useful. The most updated code and manual are attached here ancom2.zip (110.1 KB).