Understanding the meaning of beta diversity in shotgun data

[sooni]

Hello.
I performed beta diversity significance with my shotgun data using QIIME2-shotgun distribution.
However, I'm not sure how to understand this result.
The picture below shows the qzv file of beta diversity significance I performed through QIIME2 viewer.

My shotgun data consists of three experimental and control groups. I don't know why there is n=9 in each boxplot in beta diversity using my shotgun data.
I need help understanding n=9.

Thank you for your help!

[Nicholas_Bokulich]

Hi @sooni ,

Interpretation of beta diversity/group significance plots is the same as for beta diversity of any other data type. This is a common question, so much so that it is in our FAQs (which you should check if you have not seen them already):

Frequent Questions and "Best of the QIIME 2 Forum"

The following is a list of frequently asked questions on the forum, with answers, to serve as a point of reference for forum users to quickly find answers, or for forum users and moderators to use as a reference when helping others. Note: some of these listings are collapsed lists. If you see an arrow next to a title, click the title to expand the list of topic titles related to that subject. FAQs What is a "Feature" exactly? MemoryError with q2-feature-classifier How a…

This topic is listed in the FAQs, giving an explanation of how to interpret the sample sizes:

Unifrac Significant Group over-inflating n's

Hey @saatkinson, Thanks! I was able to re-run your command to look at the results. For the figures, the n doesn't represent the number of samples, but rather the number of pairwise comparisons that make up the distribution for the metric that the box-plot represents. For example, your 2920X_Control vs 2920X_Control has a sample-size of 7, and so the number of possible pairwise comparisons would be \frac{7 * (7-1)}{2} = 21 which matches what we see in the second figure. To state it a…

I hope that clarifies. Good luck!