Simrank: Rapid and sensitive general-purpose k-mer search tool

BACKGROUND: Terabyte-scale collections of string-encoded data are expected from consortia efforts such as the Human Microbiome Project http://nihroadmap.nih.gov/hmp. Intra- and inter-project data similarity searches are enabled by rapid k-mer matching strategies. Software applications for sequence d...

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Veröffentlicht in:BMC Ecology 2011-04, Vol.11 (1), p.11-11
Hauptverfasser: DeSantis, Todd Z, Keller, Keith, Karaoz, Ulas, Alekseyenko, Alexander V, Singh, Navjeet NS, Brodie, Eoin L, Pei, Zhiheng, Andersen, Gary L, Larsen, Niels
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Sprache:eng
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Zusammenfassung:BACKGROUND: Terabyte-scale collections of string-encoded data are expected from consortia efforts such as the Human Microbiome Project http://nihroadmap.nih.gov/hmp. Intra- and inter-project data similarity searches are enabled by rapid k-mer matching strategies. Software applications for sequence database partitioning, guide tree estimation, molecular classification and alignment acceleration have benefited from embedded k-mer searches as sub-routines. However, a rapid, general-purpose, open-source, flexible, stand-alone k-mer tool has not been available. RESULTS: Here we present a stand-alone utility, Simrank, which allows users to rapidly identify database strings the most similar to query strings. Performance testing of Simrank and related tools against DNA, RNA, protein and human-languages found Simrank 10X to 928X faster depending on the dataset. CONCLUSIONS: Simrank provides molecular ecologists with a high-throughput, open source choice for comparing large sequence sets to find similarity.
ISSN:1472-6785
1472-6785
DOI:10.1186/1472-6785-11-11