Hey there, fellow researchers! Have you ever found yourself scratching your head over PERMANOVA results, wondering how to report significance when the p-value keeps changing with each permutation test run? I’ve been there too!
I’m working on a microbiome beta diversity analysis using Bray-Curtis distances calculated from a phyloseq object in R. I have 2 groups (treatment vs control) with 16 samples each. To test whether diet groups have significantly different microbial communities, I’m using the adonis2() function from the vegan package. But here’s the thing: each time I run the code, the p-value (Pr(>F)) is slightly different — sometimes below 0.05, sometimes not.
So, how do we report significance in this case? Should we take the average p-value? Or should we report the range of p-values obtained?
In this post, I’ll share my simplified code and explore ways to interpret PERMANOVA results with confidence.