BEDOPS: high-performance genomic feature operations

• DOI: 10.1093/bioinformatics/bts277
• Publication Date: 2012-05-11T00:28:30Z
• Authors: Shane Neph; M. Scott Kuehn; Alex P. Reynolds; Eric Haugen; Robert E. Thurman; Audra K. Johnson; Eric Rynes; Matthew T. Maurano; Jeff Vierstra; Sean Thomas; Richard Sandstrom; Richard Humbert; John A. Stamatoya...
• Keywords: 0303 health sciences; 03 medical and health sciences; Genomics; Data Compression; Software

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: [e-mail] and [e-mail] Supplementary information: Supplementary data are available at Bioinformatics online.