Pre-trained silva classifier (V3-V4) qiime 2021.4

[SoilRotifer (Mike Robeson)]

@Maryam_21

Thank you very much for helping may I ask is it 99% or 97% for referencing

This really has no meaning, as I've outlined:

@SoilRotifer

Anyway, the old way of pre-clustering reference reads to 97% or 94% sequence similarity (as done with Greengenes and SILVA) was simply a logistical way to reduce the size of the reference database even further, so that it'll run on computers with limited memory and cpu power.

Furthermore:

@SoilRotifer

If possible, it is best to try and use reference reads that have been minimally clustered or simply dereplicated, i.e. at 99% or 100% similarity. As you'll be able to more accurately classify your reads, that is you have more reference data to use.

So, if you are using reference reads that are 99% - 100% then you can use them to classify any reads that are clustered at different similarities, e.g. 97%, 94%, etc...

In fact, some consider classifying 97% clustered OTUs against a 97% clustered reference database not a great idea. That is, as your nearest reference sequence can be up to 6% away, further reducing classification.

Does this help?