I am moving my first steps with Qiime 2 on 16S data, but I am a bit lost when moving from denoising the data with deblur to clustering (using vsearch?)
So far, so good. Now I am am not sure what to do next:
A) Is it worth doing OTU clustering using one of the three strategies with vsearch? Deblur output should be already dereplicated and filtered for chimeras;
OR
B) Should I just proceed to assigning taxonomy and move to alpha and beta diversity? For what I understand, Q2 developers are trying to move away from OTU clustering using vsearch.
Nope. Denoising is replacing OTU clustering. I broke down a couple ideas with clustering and denosing here and here a bit ago, so those threads might be helpful.
Deblur's filtering stragedy means that chimeras should get handled there. By the way, chimera slaying is mostly built into DADA2 as well, and is used by default in the QIIME 2 implementation, so if you run DADA2, you don't need to do additional chimera slaying.
I think this is the field in general. ASVs give you more specificity at very little cost, which is nice? And so, if its still cheap and mostly feasible to get ASVs, keep most of your data, and combine (most) datasets, why not?
...All of which is a long winded way of saying the option B is probably your best bet.