BEDOPS: high-performance genomic feature operations

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Zeitschriftentitel:	Bioinformatics
Personen und Körperschaften:	Neph, Shane, Kuehn, M. Scott, Reynolds, Alex P., Haugen, Eric, Thurman, Robert E., Johnson, Audra K., Rynes, Eric, Maurano, Matthew T., Vierstra, Jeff, Thomas, Sean, Sandstrom, Richard, Humbert, Richard, Stamatoyannopoulos, John A.
In:	Bioinformatics, 28, 2012, 14, S. 1919-1920
Format:	E-Article
Sprache:	Englisch
veröffentlicht:	Oxford University Press (OUP)
Schlagwörter:	Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability

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Zusammenfassung:	<jats:title>Abstract</jats:title> <jats:p>Summary: The large and growing number of genome-wide datasets highlights the need for high-performance feature analysis and data comparison methods, in addition to efficient data storage and retrieval techniques. We introduce BEDOPS, a software suite for common genomic analysis tasks which offers improved flexibility, scalability and execution time characteristics over previously published packages. The suite includes a utility to compress large inputs into a lossless format that can provide greater space savings and faster data extractions than alternatives.</jats:p> <jats:p>Availability: http://code.google.com/p/bedops/ includes binaries, source and documentation.</jats:p> <jats:p>Contact: sjn@u.washington.edu and jstam@u.washington.edu</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p>
Umfang:	1919-1920
ISSN:	1367-4811 1367-4803
DOI:	10.1093/bioinformatics/bts277