can I get the pcoa data of beta diversity data, and then I draw the PCA figure of beta diversity by myself?

After I use the command

qiime diversity core-metrics-phylogenetic
–i-phylogeny rooted-tree.qza
–i-table table.qza
–p-sampling-depth 30360
–m-metadata-file …/manifest_file
–output-dir core-metrics-results
I have got a lot results of alpha diversity and beta diversity.
And I have some comfusing as below:

  1. For beta diversity, the file “weighted_unifrac_emperor.qzv” is the visulalization of the file “weighted_unifrac_pcoa_results.qza”. Then what’s the file “weighted_unifrac_distance_matrix.qza” for and what does this file illustrate?
  2. can I extract the component of the PCOA, and i draw the PCA figure by my self?
  3. I want to cluster the samples according to the PCA, how can I make it ?
1 Like

Hi @carolhuaxia,

When you run core-metrics-phylogenetic you’re running several steps. This part of the work flow is equilivant to

  1. First, you take your tree and rarified feature table and gives you a distance matrix (“weighted_unifrac_distance_matrix.qza”). This is equivalent to qiime diversity beta-phylogenetic.
  2. Then, you calculate the ordination (PCoA coordinates). This takes your distance matrix and returns the pcoa artifact (weighted_unifrac_pcoa_results.qz). It’s the same as qiime diversity pcoa. In this step, we take the data and twist and compress the distances in ordination space to make highly dimensional space into something our little human brains can understand. Hopefully, it helps us see patterns!
  3. Finally, you visualize the PCoA to give you the visualization (weighted_unifrac_emperor .qzv). This step could be performed by the qiime emperor pcoa command. The file shows the distribution of your samples.

Yep! You can use the qiime2R package (there are so many threads on the forum about it), or export the object to a text file and then open in your favorite program.

I’m not entirely sure what you mean by this? The Deicode plugin will do PCA analysis and give you an emperor plot. Standard PCA analysis isn’t recommended because euclidean distance is not an appropriate metric for microbiome data.



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