Understanding q2-clawback weights learning

Hi @biojack, thanks for your interest in q2-clawback.

Your understanding is basically correct, except that no prior weights are set to exactly zero, they’re just made very small, so there is still a possibility of classification as any of the taxa in the database. It is also impossible to reduce the probability of misclassification to zero, but using weights certainly helps.

As it turns out, we have some pre-calculated weights using only human stool samples for GTDB classifiers in our online repository here. For instance, GTDB human stool weights for 515f-806r amplicons are available here.

If that doesn’t match the version that you’re using or you have any other issues, you can build human stool weights from scratch using the very last command on the tutorial that you already mentioned. (Down below the Stilton example.)

I hope that helps, please don’t hesitate if you have any further questions.

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