16S species-level taxonomic assignment--what is the current state of the art?
I have been using dada2 and phyloseq (phangorn for trees) combination to analyze a V4 region 16s rRNA data set. I find their approach and explanations very understandable and usable since I prefer R.
I was under the impression that even full-length 16s rRNA gene sequences were inadequate to classify up to species level since closely related species within a genus can have identical 16S rRNA gene sequences.
But, turns out, intra-genomic variants of this gene within a species or even strain may allow their unambiguous identification according to this paper:
Johnson, J.S., Spakowicz, D.J., Hong, B. et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat Commun 10, 5029 (2019). https://doi.org/10.1038/s41467-019-13036-1) available at: https://rdcu.be/b5cgB
Another relevant article regarding using black box ML algorithms (random forests) versus a straightforward logistic regression is discussed in this one:
Topçuoğlu BD, Lesniak NA, Ruffin MT 4th, Wiens J, Schloss PD. A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems. mBio. 2020;11(3):e00434-20. Published 2020 Jun 9. doi:10.1128/mBio.00434-20
Since the OP has probably already moved on long since the original query, I am writing this to document relevant current references for myself and anyone researching this topic on StackExchange Bioinformatics.