Hello everyone!
I have already seen some answers to the problem of analyzing different hypervariable regions of the 16S rRNA gene. And most of them are focused on the use of deblur and q2-fragment-insertion plugins.
I performed a meta-analysis considering 10 different sets of primers applying the Closed-reference OTU picking method.
I understand that the advantage of using deblur and the q2-fragment-insertion plugin is that it allows to recover all diversity present in the samples and also obtain a better resolution.
But I have the following question from one of the reviewers of my article:
What is the rationale to use 97% OTU clustering (closed reference) but not exact sequence variance? Exact sequence variance likely can provide a better resolution on the diversity.
In my opinion, the closed reference method is robust but allows to describe the diversity of the microbial community. Do you currently consider the use of the closed reference method to perform a meta-analysis unjustifiable?
Thank you very much in advance!!
I think closed reference gets a bad rep here. Closed reference gets a bad rep in general becaue the idea of (a) discarding sequences and (b) not having something robust to multiple enviroments is unattractive to many people.
And I think it depends. I've been playing wtih some benchmarks in this area myself. ...The classifier tends to give me more unclassified reads for my ASVs which makes identification more difficult and collapsing a challenge. Do you use a per-region classifier, a bespoke classifier, a full length classifier here? (Is it approrpiate to apply different methodology to different regions and studies?) Like, these are all questions you need to ask.
I also believe a recent thread talked about how fragment insertion doesn't work as well on mixed regions (so if you're combining V3, V34, etc it might not be as effective.)
...I'll also say there's potentially some benefit in being able to look at bray curtis distance which fragment insertion doesn't allow you to do.
Hi Justine,
I used a full length sequence classifier (silva 138) to be able to compare v1-v3 against v5-v9.
So, I will explain to the reviewer that both methods currently have limitations!
Thank you very much for your answer !!