How can I compare the differeance of the diversity both all of the groups and part of the group in a cloumn of metadata.

[YuZhang]

Thank you , sir. I want to use the rarefaction normalizes data to compare the difference of alpha diversity in some group of my samples. That's mean I want a fig A1 including all groups in all my samples ,and fig A2,fig A3...including different groups in partial samples,respectively. Also , I want a pcoa graph B1 including all groups in all my samples ,and fig B2,fig B3...including different groups in partial samples,respectively..

Alpha/beta diversity: filtering datasets, additional metadata post analysis and missing metadata values

I prefer the additional metadata column — it will be more informative about overall differences within and between lakes and size fractions. beta-group-significance will perform pairwise permanova tests, so this will still tell you about whether individual fractions in individual lakes are different from each other, etc... filtering and re-analyzing will be more useful if, e.g., you do the total analysis and see differences between some groups but your PCoA plots are a nasty tangled ball... th…

I have read this post. I used the result of qiime diversity alpha by import the rarefaction normalizes data rarefied_table.qza .from core-metrics-phylogenetic . And, I change the metadata form as below:

@YuZhang

I added a new column, including samples which I need to compare. And,some samples, which I dont want to analysis , I let it empy in the cloumn.
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So my alpha diversity can be compared separately in different group.

This

filtering and re-analyzing will be more useful if, e.g., you do the total analysis and see differences between some groups but your PCoA plots are a nasty tangled ball… then you could filter and re-run with subsets for ease of visualization.

and

@ChrisKeefe

PCoA results are calculated using all of the samples provided, and each sample’s projection on the plot is influenced by all samples in the data, not just the visible samples. As such, you should be careful when making some of your samples invisible. This can be a useful tool for simplifying your view of the data, but must be explained very clearly when sharing results; a PCoA projection of all samples with some of them invisible is not the same as a PCoA projection of only the visible data, and can easily be misinterpreted.

make me realized I couldn't separate a PCOA graph into groups through metadata changes.

So,do I need to filter the feature data accroding the groups first ? Then, I should rarefied the data again through set the second sampling depth of core-metrics-phylogenetic to obtain ob rarefied_table-2.qza? But does these two sampling depth (first time is for alpha and second for beta pcoa) should to be same ?

And ,I know the process of rarefaction normalizes data is random,even if with the same depth I cant get the same result,right? So, I wanna know that alpha diversity and beta diversity (pcoa) are not using the same standardized data is that a problem?

Yu