BEDOPS: high-performance genomic feature operations

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ID: 298899
2012
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Abstract
Abstract 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. Availability: http://code.google.com/p/bedops/ includes binaries, source and documentation. Contact: sjn@u.washington.edu and jstam@u.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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Authors Shane Neph, Michael S. Kuehn, Alex Reynolds, Eric Haugen, Robert E. Thurman, Audra Johnson, Eric Rynes, Matthew T. Maurano, Jeff Vierstra, Sean Thomas, Richard Sandstrom, Richard Humbert, J Stamatoyannopoulos
Journal BMC Bioinformatics
Year 2012
DOI
10.1093/bioinformatics/bts277
URL
https://academic.oup.com/bioinformatics/article-pdf/28/14/1919/48870388/bioinformatics_28_14_1919.pdf
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