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BEDOPS: high-performance genomic feature operations
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| Zeitschriftentitel: | Bioinformatics |
|---|---|
| Personen und Körperschaften: | , , , , , , , , , , , , |
| In: | Bioinformatics, 28, 2012, 14, S. 1919-1920 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Oxford University Press (OUP)
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| Schlagwörter: |
| author_facet |
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. 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. |
|---|---|
| author |
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. |
| spellingShingle |
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. Bioinformatics BEDOPS: high-performance genomic feature operations Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability |
| author_sort |
neph, shane |
| spelling |
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. 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/bts277 <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> BEDOPS: high-performance genomic feature operations Bioinformatics |
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| title |
BEDOPS: high-performance genomic feature operations |
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BEDOPS: high-performance genomic feature operations |
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BEDOPS: high-performance genomic feature operations |
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BEDOPS: high-performance genomic feature operations |
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BEDOPS: high-performance genomic feature operations |
| title_short |
BEDOPS: high-performance genomic feature operations |
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bedops: high-performance genomic feature operations |
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Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability |
| url |
http://dx.doi.org/10.1093/bioinformatics/bts277 |
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2012 |
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1919-1920 |
| description |
<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> |
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| author | 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. |
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| description | <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> |
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| spelling | 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. 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/bts277 <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> BEDOPS: high-performance genomic feature operations Bioinformatics |
| spellingShingle | 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., Bioinformatics, BEDOPS: high-performance genomic feature operations, Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability |
| title | BEDOPS: high-performance genomic feature operations |
| title_full | BEDOPS: high-performance genomic feature operations |
| title_fullStr | BEDOPS: high-performance genomic feature operations |
| title_full_unstemmed | BEDOPS: high-performance genomic feature operations |
| title_short | BEDOPS: high-performance genomic feature operations |
| title_sort | bedops: high-performance genomic feature operations |
| title_unstemmed | BEDOPS: high-performance genomic feature operations |
| topic | Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability |
| url | http://dx.doi.org/10.1093/bioinformatics/bts277 |