qiime feature-classifier extract-reads command
Is it all rigtht if I don’t set any optional pamameters? These parameters: --p-trunc-len, --p-trim-left, --p-min-length, --p-max-length, I have no idea what value fit best. For example, my sequences have been trimmed to 150bp in previous deblur step, now how can I set these parameters?
Thank you very much for your kindly help in advance!
If your target amplicons match or are internal to the sequences used to train the classifier. So if you use any 16S amplicon, you can use the full-length classifiers. Or…
Yes, you can use either of the classifiers trained on amplicons targeted with these primers, e.g., gg-13-8-99-515-806-nb-classifier.qza
Yes, see the notes in the “training a feature classifier” tutorial.
You could set trunc-len to 150 and it may slightly boost classifier accuracy — but the boost would only be ever so slight so if you are using the 515f-806r primers (EMP) you should just use the pre-trained classifiers and save some time!
Thanks a lot! @Nicholas_Bokulich
My primers are V4 515f-806r primers(EMP), I can use both Greengenes 13_8 99% OTUs from 515F/806R region of sequences and Greengenes 13_8 99% OTUs full-length sequences pre-trained classifier, right? Does the 515F/806R pre-trained classifier classify better than full length pre-trained classifier? What’s the difference of using these two pre-trained classifier?