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K-SLAM: accurate and ultra-fast taxonomic classification and gene identification for large metagenomic data sets.


ABSTRACT: k-SLAM is a highly efficient algorithm for the characterization of metagenomic data. Unlike other ultra-fast metagenomic classifiers, full sequence alignment is performed allowing for gene identification and variant calling in addition to accurate taxonomic classification. A k-mer based method provides greater taxonomic accuracy than other classifiers and a three orders of magnitude speed increase over alignment based approaches. The use of alignments to find variants and genes along with their taxonomic origins enables novel strains to be characterized. k-SLAM's speed allows a full taxonomic classification and gene identification to be tractable on modern large data sets. A pseudo-assembly method is used to increase classification accuracy by up to 40% for species which have high sequence homology within their genus.

SUBMITTER: Ainsworth D 

PROVIDER: S-EPMC5389551 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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k-SLAM: accurate and ultra-fast taxonomic classification and gene identification for large metagenomic data sets.

Ainsworth David D   Sternberg Michael J E MJE   Raczy Come C   Butcher Sarah A SA  

Nucleic acids research 20170201 4


k-SLAM is a highly efficient algorithm for the characterization of metagenomic data. Unlike other ultra-fast metagenomic classifiers, full sequence alignment is performed allowing for gene identification and variant calling in addition to accurate taxonomic classification. A k-mer based method provides greater taxonomic accuracy than other classifiers and a three orders of magnitude speed increase over alignment based approaches. The use of alignments to find variants and genes along with their  ...[more]

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