Strain-level metagenomic assignment and compositional estimation for long reads with MetaMaps.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
11 07 2019
Historique:
received: 07 12 2018
accepted: 11 06 2019
entrez: 13 7 2019
pubmed: 13 7 2019
medline: 28 10 2019
Statut: epublish

Résumé

Metagenomic sequence classification should be fast, accurate and information-rich. Emerging long-read sequencing technologies promise to improve the balance between these factors but most existing methods were designed for short reads. MetaMaps is a new method, specifically developed for long reads, capable of mapping a long-read metagenome to a comprehensive RefSeq database with >12,000 genomes in <16 GB or RAM on a laptop computer. Integrating approximate mapping with probabilistic scoring and EM-based estimation of sample composition, MetaMaps achieves >94% accuracy for species-level read assignment and r

Identifiants

pubmed: 31296857
doi: 10.1038/s41467-019-10934-2
pii: 10.1038/s41467-019-10934-2
pmc: PMC6624308
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3066

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Auteurs

Alexander T Dilthey (AT)

Institute of Medical Microbiology and Hospital Hygiene, Heinrich-Heine-University Düsseldorf, Düsseldorf, North Rhine-Westphalia, Germany. alexander.dilthey@med.uni-duesseldorf.de.
Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, 20892, USA. alexander.dilthey@med.uni-duesseldorf.de.

Chirag Jain (C)

Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, 20892, USA.
Georgia Institute of Technology, Atlanta, GA, 30332, USA.

Sergey Koren (S)

Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, 20892, USA.

Adam M Phillippy (AM)

Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, 20892, USA.

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Classifications MeSH