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