NanoCLUST: a species-level analysis of 16S rRNA nanopore sequencing data

• Published in: Bioinformatics (Oxford, England) Vol. 37; no. 11; pp. 1600 - 1601
• Main Authors: Rodríguez-Pérez, Héctor, Ciuffreda, Laura, Flores, Carlos
• Format: Journal Article
• Language: English
• Published: Oxford University Press 12.07.2021
• ISSN: 1367-4803; 1367-4811; 1367-4811
• DOI: 10.1093/bioinformatics/btaa900

Abstract Summary 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. Availability and implementation Source code, test data and documentation of NanoCLUST are freely available at https://github.com/genomicsITER/NanoCLUST under MIT License. Supplementary information Supplementary data are available at Bioinformatics online.