Doubt about statistical test

Good morning to all,
I have a doubt about the statistical test to apply of my samples.
I have samples collected from three different sites of the same animal (rumen, intestine and feces).
I have two groups of animals (control and treated).
I’d like to know if in my case it is better to calculate alpha and beta diversity with longitudinal plugin (and use Mann Withney or Wilcoxon test ?) or alpha-group significance plugin that uses the kruskal wallis test?

thank you

Please read the following before posting!

Is this post about a User Support Question? Those include questions about specific results while running QIIME 2, warnings observed while running a QIIME 2 command. Please do not post questions here that have to do with interpretation of results, general discussion, or technical support.

Before posting, please make sure you have the following information available, in order for us to help you in a timely manner:

  • Have you searched for the problem on the forum? It is rare that we see a new question asked, so make sure you do your homework before asking for us to commit our time to helping you.
  • Have you reviewed the QIIME 2 Forum Glossary?
  • Version of QIIME 2 you are running, and how it is installed (e.g. Virtualbox, conda, etc.)
  • What is the exact command or commands you ran? Copy and paste please.
  • What is the exact error message, if applicable? If you didn’t run the command with the --verbose flag, please re-run and copy-and-paste the results.

Hi @rparadiso,

It depends on the hypothesis you want to test. So, if you want to know if the individual rumens respond to the change in treatment, you would want to filter your alpha diversity or distance matrix and apply a kruskal wallis, adonis or permanova (most are implemented in q2-diversity; you can get a multivariate test for alpha diversity from anova in q2–longitudinal).

If you want to know about how the rumen/lumen/intestine differ in the same animal between the two treatments, then I would recommend the LMEs in q2-longitudinal.

When I’m doing a similar analysis, I will often mix the two techniques because they let me address different aspects of the same data.

Best,
Justine

4 Likes

This topic was automatically closed 31 days after the last reply. New replies are no longer allowed.