Thank you for your kind reply and suggestion!
To answer your question: yes, I’m looking at the genus level, like what the authors did.
I also have some update:
I tried using lower trimming lengths in DADA2, and it worked.
The raw reads are 251 bp, and they sequenced the V4 region of 16s rRNA (about 254 bp).
Previously I used CutAdapat then DADA2 with 220 and 240 bp as trimming length values, but could not detect all genera (it’s missing one genus).
I then tried DADA2 with 140, 160, 180, 200 bp as trimming length values (without CutAdapt) and these worked, but I’m not sure why they worked. Also, even though the genus in question can be detected by lowering the trimming length values, it’s feature frequency is very small (below 10).
Do you think this is because of the raw data (the reverse reads) do not have enough good quality bases after 200 bp?
Please find attached the demux file below:
Mock_QMINI_demux.qzv (291.7 KB)
I wonder if this finding would be applicable to my actual samples (whose actual genera and composition are unknown)?
Many thanks for your time and kind help!