Hi @Jeremie_Auger ,
I would see a couple different options here:
- q2-clawback and the weighted classifiers that we provide in the QIIME 2 resources were designed with exactly this problem in mind, that some species (e.g., of LAB) will be more abundant in certain environments than others, and knowing the habitat can help resolve their identification vs. genetically similar but ecologically distinct relatives. However, there are not pre-existing class weights for vaginal swab samples — you could try to follow this tutorial to generate your own, and/or adjust the weights artificially based on your own expectations (e.g., to upweight species like L. iners and downweight others that should be rare in vaginal samples): Using q2-clawback to assemble taxonomic weights
- the easiest answer to your question is to adjust the confidence threshold parameter of
classify-sklearn. You could try to reduce the threshold a bit, e.g., 0.5 would be totally reasonable. And if you really just want a top hit, set to zero confidence (obviously this is not the best option, but a very easy way to force the classifier to classify to species level)
I hope that helps!