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BEDOPS: high-performance genomic feature operations

Open access
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.·2012·Bioinformatics

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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Metadata

Authors
Neph, S., Kuehn, M. S., Reynolds, A. P., Haugen, E., Thurman, R. E., Johnson, A. K., Rynes, E., Maurano, M. T., Vierstra, J., Thomas, S., Sandstrom, R., Humbert, R., & Stamatoyannopoulos, J. A.
Venue
Bioinformatics
Published
2012-05-09
Volume
28
Issue
14
Pages
1919-1920
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2119451273
Cited by
1,010
References
3
FWCI
7.43
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: BEDOPS: high-performance genomic feature operations. https://app.cochat.ai/papers/10.1093/bioinformatics/bts277
The paper
Neph, S., Kuehn, M. S., Reynolds, A. P., Haugen, E., Thurman, R. E., Johnson, A. K., Rynes, E., Maurano, M. T., Vierstra, J., Thomas, S., Sandstrom, R., Humbert, R., & Stamatoyannopoulos, J. A. (2012). BEDOPS: high-performance genomic feature operations. Bioinformatics. https://doi.org/10.1093/bioinformatics/bts277

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.