Simrank: Rapid and sensitive general-purpose k-mer search tool |
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| Authors: | Todd Z DeSantis Keith Keller Ulas Karaoz Alexander V Alekseyenko Navjeet NS Singh Eoin L Brodie Zhiheng Pei Gary L Andersen Niels Larsen |
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| Affiliation: | (1) Ecology Department, Lawrence Berkeley National Laboratory, Berkeley, USA;(2) Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, USA;(3) Department of Microbiology, New York University School of Medicine, New York, USA;(4) Department of Molecular Biology, Aarhus University, Aarhus, Denmark;(5) Center for Health Informatics and Bioinformatics, New York University Langone Medical Center, New York, USA |
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| Abstract: | Background Terabyte-scale collections of string-encoded data are expected from consortia efforts such as the Human Microbiome Project . 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. |
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