We have two simple questions about the feasibility of using q2-diversity plugin for statistical analysis of picrust2 inferred data:
- We applied this tutorial https://github.com/picrust/picrust2/wiki/q2-picrust2-Tutorial to a simple dataset (three groups of soil microbiomes, n=5). We used q2-diversity on the q2-picrust2 output, to test for significant differences on ”potential community functions” among the three treatments:
qiime diversity core-metrics
qiime diversity beta-group-significance
We used a PERMANOVA test to check for differences in “inferred functional pathways” at community level, using Jaccard and Bray-Curtis index. In principle I don’t see a problem from a conceptual point of view (this is also compositional data), but we would be very happy to read your opinion about this! In case this was not a good idea, do you suggest any alternative to get an “overall” result?
- PERMANOVA results indicated non-significant differences with Bray-Curtis index. But with Jaccard index, although the global PERMANOVA test was not significant, in the pairwise comparison we got a very interesting result, when comparing two treatments (p<0.05) what is meaningful for us. Is it then correct to use the pairwaise comparisons when the global PERMANOVA test is not significant? (also important to know when analyzing ASVs). See attached qzv.
Treatment-jaccard-sign.qzv (339.1 KB)
Thanks in advance for your inputs!