downstream analysis of q2-perc-norm results in QIIME 2

[cduvallet (Claire Duvallet)]

Thanks for the ping @gregcaporaso. Unfortunately there are no updated recommendations because this isn't a software issue so much as a scientific one. The fact that FeatureTable[PercentileNormalized] artifacts are not a valid input to any other QIIME2 function is by design (it's a feature, not a bug! ).

As we discuss in the README and this forum post, percentile normalized data was designed to address batch effects for differential abundance testing. If you want to use it for something else, you'd have to think through the statistical assumptions of those downstream analyses and make sure that the output data from percential normalization is an appropriate input.

Two other older posts tangentially addressing this question:

• Is percentile-normalized data appropriate for UniFrac?
• diversity metrics and batch effects - #5 by seangibbons

Actually, I think @seangibbons said it best in that last post:

@seangibbons

The original application of percentile normalization is differential abundance testing on a taxon-by-taxon basis (i.e. is ‘taxon X’ enriched/depleted in cases vs. controls). It works well in this application, but extreme caution is advised for other use cases.