Hello,
Can anyone explain how to identify the sources of variation represented in the axes of an emperor plot?
Thank you!
Hello,
Can anyone explain how to identify the sources of variation represented in the axes of an emperor plot?
Thank you!
Hi @danielee,
I’m not totally sure I understand your question, but I’ll take a stab? The number represents the amount of variation explained. But, because of hte way PCoA works, there’s not factor loading ro something similar for most distance metrics. You could try a biplot, which will show the location of organsims in PCoA space. However, there’s variability utility there: often the most abundant taxa (which are frequently visualized) are not the factors which are driving seperation. You could look into DECOIDE, which is a plug in based on PCA, rather than PCoA and can provide a better sense of factor loading.
Best,
Justine
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