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really appreciate your help on this. I have a data matrix of relative abundance of 20 taxa identified at the genus level via 16s. They belong to 100 human subjects. Subjects were randomly grouped into 5 treatments (20 subjects per treatment). Microbiome 16s was measured at 4 timepoints. So basically data can be organized as follows: 100 subjects, 5 treatment (20 subjects per treatment), 4 timepoints per treatment.
MY QUESTION: When running betadispers prior to PERMANOVA, I get a significant P-value for the treatment factor, but not for timepoints within treatment.
Should I run a Permanova for every treatment group independently given the fact that treatment factor does not meet the assumption for Permanova?
This discussion was converted from issue #649 on May 18, 2024 12:34.
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really appreciate your help on this. I have a data matrix of relative abundance of 20 taxa identified at the genus level via 16s. They belong to 100 human subjects. Subjects were randomly grouped into 5 treatments (20 subjects per treatment). Microbiome 16s was measured at 4 timepoints. So basically data can be organized as follows: 100 subjects, 5 treatment (20 subjects per treatment), 4 timepoints per treatment.
MY QUESTION: When running betadispers prior to PERMANOVA, I get a significant P-value for the treatment factor, but not for timepoints within treatment.
Should I run a Permanova for every treatment group independently given the fact that treatment factor does not meet the assumption for Permanova?
Any help/suggestion would be greatly appreciated.
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