There’s an example used the Core concepts document section discussing semantic types pointing out that you could run a quantitative distance method with qualitative data, but you shouldn’t, so QIIME’s semantic formatting ensures you don’t do something unintended.
I’m interested in using a Bray-Curtis distance calculation on binary (presence-absence) data. The initial feature table was collapsed with
qiime feature-table presence-absence, but when I try to incorporate that into
qiime diversity beta the error suggests that it’s looking for a table with relative abundances, not just 0’s and 1’s.
Plugin error from diversity: Argument to parameter 'table' is not a subtype of FeatureTable[Frequency].
I couldn’t find anything in the forum or documentation that suggested how to use presence-absence data. Usually if I can’t find anyone asking the question, or any documentation, it means I’m making a terribly incorrect assumption about how to use a dataset appropriately!
Nevertheless, in this one case I feel pretty confident this is because most QIIME users are dealing with microbial datasets where relative abundances are an acceptable input for a distance method. However my dataset is generated from insect COI sequence data, and I am a bit skeptical about using read abundances to make ecological inferences in alpha and beta diversity measures. If nothing else, I’m happy to explore using the quantitative approaches, but I have to at least also explore the qualitative inputs using presence-absence data.
If there are any suggestions about how to incorporate presence-absence data into diversity calculations in QIIME I’d love to find out more. Perhaps my only alternative is to export the binary matrix and perform the analyses in something like
vegan in R (or an equivalent Python package). If that is the case, it would be great to know if there is a way to compute the distance matrix externally, but still be able to bring in that matrix back into QIIME for the
qiime diversity beta-group-significance function.