I’m interested in comparing different taxonomical assignations of 16s rRNA data regarding classifiers (blast, sklearn, vsearch) or for example sklearn trained or not. I would like to use a command like “compare_taxa_summaries.py” from Qiime1. I have been looking for similar options in Qiime2 but with no luck.
All of this comes from my interest in assessing what might be the best option to assign taxonomy to V3 and V4 regions from 16s rRNA gene. I know best option should be a pre-trained classifier in these regions, but just wanted to confirm it and compare different taxonomy outputs.
Therefore, is there a command like the one from Qiime1? Should be different classification options be of concern? How can this be assessed?
Also, I’m sorry if this is not “technical support” at all. There’s a bit of general discussion as well.
Thank you in advance!!
And a real live example using a mock community at the end of this tutorial
Note that these methods were designed for use with mock communities or other datasets where the composition is known, since the outputs are accuracy metrics. However, it would be possible to use these methods to compare taxonomy classifications of samples with unknown compositions and the outputs essentially become measures of how similar those taxonomy classifications are.
Thank you very much for helping!
Therefore, after assessing classifications similarity, would be possible to check the reliability of the old classifier and the new (improved) one against some known community? (I am working with 16S from nasal swabs in pigs).
Thanks in advance!
Sure, if you have a known community you would use the actions in q2-quality-control to measure various accuracy metrics, then compare those between old and new classifiers.