Possible Analysis Pipeline for Ion Torrent 16S Metagenomics Kit Data in QIIME2?

[Nicholas_Bokulich]

Hi @cjone228,

@cjone228

We just wanted to check and see if A) this is an acceptable way to move forward

The workflow you've described looks okay to me at first glance... I have not worked with ion torrent data or this kit, but based on my understanding this all seems fine.

@cjone228

B) if anyone has any further ideas on how we could separate the amplicons

I don't think I can add anything to what has already been discussed in several topics on the forum — e.g., the one you linked to above. Not having the primers complicates this. This makes q2-quality-control the best approach for separating... you would need to create reference sequences trimmed to the variable regions you know you have (even if you don't have the exact primers) and try to grab out reads that are close enough matches (be lenient with the perc-identity and coverage parameters)

@cjone228

• @Nicholas_Bokulich in your reply to the thread here , you suggest this classifier for Ion Torrent data but later suggest VSEARCH instead. Could you please clarify?

I clarified at the bottom of that post:

@Nicholas_Bokulich

Honestly, it is probably better to stick with vsearch for your case, where there are two issues to overcome for the sklearn classifier:

1. reads in mixed orientations
2. a mixture of primers. It sounds like these effectively cover most of the 16S rRNA gene, so the pre-trained full-length 16S classifier would be your best best. You will not be able to capture the slight accuracy boost that comes from training to the specific primer sites.

@cjone228

One new method we saw was SMURF. Any thoughts on that, anyone? Again, we do not have the primer sequences.

I think you maybe need to know your primers for SMURF??? @jwdebelius may provide better advice regarding SMURF.

Good luck!