Reducing storage requirements for biological sequence comparison
Motivation: Comparison of nucleic acid and protein sequences is a fundamental tool of modern bioinformatics. A dominant method of such string matching is the ‘seed-and-extend’ approach, in which occurrences of short subsequences called ‘seeds’ are used to search for potentially longer matches in a l...
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Veröffentlicht in: | Bioinformatics 2004-12, Vol.20 (18), p.3363-3369 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Motivation: Comparison of nucleic acid and protein sequences is a fundamental tool of modern bioinformatics. A dominant method of such string matching is the ‘seed-and-extend’ approach, in which occurrences of short subsequences called ‘seeds’ are used to search for potentially longer matches in a large database of sequences. Each such potential match is then checked to see if it extends beyond the seed. To be effective, the seed-and-extend approach needs to catalogue seeds from virtually every substring in the database of search strings. Projects such as mammalian genome assemblies and large-scale protein matching, however, have such large sequence databases that the resulting list of seeds cannot be stored in RAM on a single computer. This significantly slows the matching process. Results: We present a simple and elegant method in which only a small fraction of seeds, called ‘minimizers’, needs to be stored. Using minimizers can speed up string-matching computations by a large factor while missing only a small fraction of the matches found using all seeds. |
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ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/bth408 |