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How to use qiime group_significance.py script?

Hi all!

I know that maybe this is not a question for this forum but I will be glad if somebody could give me an advice in that.

I would like to compare bacteria abundances (otu_table.biom, qiime) for two groups of samples:

  • 35 samples with disease

  • 15 controls

I am not sure which test from group_significance.py script should I use. I have a clinical data that need to be correlated with and between those groups.

Do you think that I need to check data for normal distribution? (for every question from clinical data)

Or can I just go with non-parametric test? (eg. Mann-Whitney test).

What test do you use in similar situations?

I will be happy for suggestions.

Best,

Agata

qiime
• 3,087 views • link
written by agata88 agata88

I have never tried the group_significance.py but I guess the UNIFRAC comparison will give you a good idea on your comparison,

http://qiime.org/scripts/beta_significance.html

If you have done the pick_de_novo pipeline, you will have the outputs for beta significance.

• 0 views • link
written by sridhar56 sridhar56

I don't think this will help ... especially when I need to compare eg 35 vs 15 samples. I think I need to use group_significance.py script with specified mapping file. I just don't know if I need to check data for normal distribution. Can I assume that all data is not normally distributed? (because of small number of sample size) and do the non-parametric test ...

• 0 views • link
written by agata88 agata88

Actually I got that wrong, the one I pointed to you was unweighted, you can do the beta diversity which requires a mapping file,

Try this,

http://qiime.org/scripts/beta_diversity.html

I have analyzed many samples this way and through this script, you can have unequal number of samples as long as there are 2 groups.

• 0 views • link
written by sridhar56 sridhar56

This looks good ... I think I am going to use that first, thank you :)

• 0 views • link
written by agata88 agata88

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