ASV prediction
Exact ASV prediction prove to be a good alternative to OTU picking (Callahan, B. J. et al 2016 1). The process infers sample sequences exactly and resolve differences to as little as one nucleotide sequences. This approach allows for more accurate taxonomic classification and has additional benefits such as the reuse of previously processed sample ASVs in future projects (Callahan, B. J. et al 2017 2). DADA2 is an R package that contains a complete pipeline read processing, ASV prediction and classification. QIIME2 has a DADA2 interface though there might be limitations on what settings can be configured when running through QIIME2 and not natively through R.
Software: DADA2, QIIME2
Bibliography
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Callahan, B. J., et al. “DADA2: High-resolution sample inference from Illumina amplicon data.” Nature methods, 13.7 (2016), 581-3. ↩
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Callahan, B. J., et al. “Exact sequence variants should replace operational taxonomic units in marker-gene data analysis.” The ISME journal, 11(12), 2639-2643. ↩
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