Litcius/Paper detail

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

Hector Rodríguez‐Pérez, Laura Ciuffreda, Carlos Flores

2020Bioinformatics143 citationsDOI

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.

Topics & Concepts

Computer scienceSource codeAmpliconMIT LicensePipeline (software)Nanopore sequencingDocumentationSoftwarePattern recognition (psychology)Cluster analysisData miningIdentification (biology)Projection (relational algebra)Artificial intelligenceCode (set theory)AlgorithmDNA sequencingBiologyProgramming languagePolymerase chain reactionGeneSet (abstract data type)DNABiochemistryGeneticsBotanyGenomics and Phylogenetic StudiesMicrobial Community Ecology and PhysiologyGut microbiota and health