BEDOPS: high-performance genomic feature operations | Zendy

Shane Neph | Zendy; Michael S. Kuehn | Zendy; Alex Reynolds | Zendy; Eric Haugen | Zendy; Robert E. Thurman | Zendy; Audra Johnson | Zendy; Eric Rynes | Zendy; Matthew T. Maurano | Zendy; Jeff Vierstra | Zendy; Sean Thomas | Zendy; Richard Sandstrom | Zendy; Richard Humbert | Zendy; J Stamatoyannopoulos | Zendy

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BEDOPS: high-performance genomic feature operations

Author(s) -

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

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts277

Subject(s) - computer science , suite , scalability , documentation , software , flexibility (engineering) , source code , feature (linguistics) , software suite , data mining , code (set theory) , lossless compression , database , programming language , data compression , artificial intelligence , linguistics , statistics , philosophy , mathematics , archaeology , set (abstract data type) , history

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.

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