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k-SLAM: Accurate and ultra-fast taxonomic classification and gene identification for large metagenomic datasets

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Title: k-SLAM: Accurate and ultra-fast taxonomic classification and gene identification for large metagenomic datasets
Authors: Ainsworth, D
Sternberg, MJE
Raczy, C
Butcher, SA
Item Type: Journal Article
Abstract: k-SLAM is a highly e cient algorithm for the characterisa- tion of metagenomic data. Unlike other ultra-fast metage- nomic classi ers, full sequence alignment is performed allow- ing for gene identi cation and variant calling in addition to accurate taxonomic classi cation. A k -mer based method provides greater taxonomic accuracy than other classi ers and a three orders of magnitude speed increase over align- ment based approaches. The use of alignments to nd vari- ants and genes along with their taxonomic origins enables novel strains to be characterised. k-SLAM's speed allows a full taxonomic classi cation and gene identi cation to be tractable on modern large datasets. A pseudo-assembly method is used to increase classi cation accuracy by up to 40% for species which have high sequence homology within their genus.
Issue Date: 13-Dec-2016
Date of Acceptance: 28-Nov-2016
URI: http://hdl.handle.net/10044/1/43100
DOI: https://dx.doi.org/10.1093/nar/gkw1248
ISSN: 1362-4962
Publisher: Oxford University Press (OUP)
Start Page: 1649
End Page: 1656
Journal / Book Title: Nucleic Acids Research
Volume: 45
Issue: 4
Copyright Statement: © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: Medical Research Council (MRC)
Funder's Grant Number: MR/L01632X/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Developmental Biology
05 Environmental Sciences
06 Biological Sciences
08 Information And Computing Sciences
Publication Status: Published
Appears in Collections:Department of Surgery and Cancer
Faculty of Natural Sciences