greengenes database

[Nicholas_Bokulich]

correct, use one of the pre-trained classifiers

might I note: training your own classifier could be highly beneficial. I have used the HOMD database in the past for saliva bacterial classification with q2-feature-classifier; it is an oral microbiome-specific database and using it together with q2-feature-classifier will increase likelihood of species-level classification. Worth comparing vs. greengenes or silva.

If you're up for a challenge (that will increase species classification accuracy even more) you could also try training a classifier with oral microbiome-specific taxonomic weights, as described in this tutorial:

Using q2-clawback to assemble taxonomic weights

Note: This guide assumes you have installed QIIME 2 using one of the procedures in the install documents. This tutorial extends the q2-feature-classifier tutorial to show how you can improve taxonomic classification accuracy by assembling ecologically informed taxonomic weights for your samples using q2-clawback. This approach is described in this article: https://doi.org/10.1038/s41467-019-12669-6 We will retrain the naive Bayes classifier from the q2-feature-classifier to classify the ski…

You could follow that tutorial with either the HOMD or greengenes or SILVA sequences. See the "more exotic weights" section and swap out this line:

redbiom search metadata "cheese where cheese_type=='stilton'" > sample_ids

for this:

redbiom search metadata "where host_taxid==9606 and sample_type in ('Oral', 'oral', 'Mouth', 'mouth', 'Saliva', 'saliva')" > sample_ids