Hi everyone! I am a new user, and I hope to discuss the following problems with you!
(My qiime2 version is 2020.6, platform is Ubuntu 18.04.)
I used both dada2 and deblur to denoise the samedata. After annotation, I found that the results were quite different (as follow.
demux result is like this
I kept the 10-220 forward reads and 0-220 reverse read to proceed the dada2, the result goes like
I kept the 0-300 joined-read to proceed the deblur, the result goes like
I tried a lot of lengths of cuts but the results didn't vary much, it showed defferent beween dada2 and deblur after feature classifier. I guess it has something to do with the classifier I chose. I sequenced the V3-V4 16s RNA region but used the full length classifier posed on qiime2 official website "silva-138-99-nb-classifier.qza".
I would like to ask if the reason why Dada and Deblur are very different is the problem of my classifier selection or the problem of data processing.
- Here is the code I use to proceed with the data
qiime vsearch join-pairs
qiime quality-filter q-score-joined
time qiime deblur denoise-16S
time qiime dada2 denoise-paired
qiime feature-classifier classify-sklearn
Waiting for your help!
thanks and hope you have a wonderful day !!