Journal
BIOINFORMATICS
Volume 37, Issue 11, Pages 1600-1601Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa900
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Funding
- Instituto de Salud Carlos III [PI14/00844, PI17/00610, FI18/00230]
- European Regional Development Funds, `A way of making Europe' from the European Union
- Ministerio de Ciencia e Innovacion (AEI/FEDER, UE) [RTC-2017-6471-1]
- Cabildo Insular de Tenerife [CGIEU0000219140]
- Fundacion Canaria Instituto de Investigacio' n Sanitaria de Canarias [PIFUN48/18]
- Instituto Tecnolo' gico y de Energi'as Renovables (ITER) [OA17/008]
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NanoCLUST is an analysis pipeline that outperforms other state-of-the-art software in accurately characterizing bacterial identification and abundance profile estimation at the species level, demonstrating its effectiveness with two commercial mock communities.
NanoCLUST is an analysis pipeline for the classification of amplicon-based full-length 16S rRNA nanopore reads. It is characterized by an unsupervised read clustering step, based on Uniform Manifold Approximation and Projection (UMAP), followed by the construction of a polished read and subsequent Blast classification. Here, we demonstrate that NanoCLUST performs better than other state-of-the-art software in the characterization of two commercial mock communities, enabling accurate bacterial identification and abundance profile estimation at species-level resolution.
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