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BugSeq 16S: NanoCLUST with Improved Consensus Sequence Classification

Jung, A.; Chorlton, S. D.

2021-03-17 bioinformatics
10.1101/2021.03.16.434153 bioRxiv
Show abstract

NanoCLUST has enabled species-level taxonomic classification from noisy nanopore 16S sequencing data for BugSeqs users and the broader nanopore sequencing community. We noticed a high misclassification rate of NanoCLUST-derived consensus 16S sequences due to its use of BLAST top hit taxonomy assignment. We replaced the consensus sequence classifier of NanoCLUST with QIIME2s VSEARCH-based classifier to enable greater accuracy. We use mock microbial community and clinical 16S sequencing data to show that this replacement results in significantly improved nanopore 16S accuracy (over 5% recall and 19% precision), and make this new tool (BugSeq 16S) freely available for academic use at BugSeq.com/free.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.