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Sambamba: fast processing of NGS alignment formats
Summary: Sambamba is a high-performance robust tool and library for working with SAM, BAM and CRAM sequence alignment files; the most common file formats for aligned next generation sequencing data. Sambamba is a faster alternative to samtools that exploits multi-core processing and dramatically red...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4765878/ https://www.ncbi.nlm.nih.gov/pubmed/25697820 http://dx.doi.org/10.1093/bioinformatics/btv098 |
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author | Tarasov, Artem Vilella, Albert J. Cuppen, Edwin Nijman, Isaac J. Prins, Pjotr |
author_facet | Tarasov, Artem Vilella, Albert J. Cuppen, Edwin Nijman, Isaac J. Prins, Pjotr |
author_sort | Tarasov, Artem |
collection | PubMed |
description | Summary: Sambamba is a high-performance robust tool and library for working with SAM, BAM and CRAM sequence alignment files; the most common file formats for aligned next generation sequencing data. Sambamba is a faster alternative to samtools that exploits multi-core processing and dramatically reduces processing time. Sambamba is being adopted at sequencing centers, not only because of its speed, but also because of additional functionality, including coverage analysis and powerful filtering capability. Availability and implementation: Sambamba is free and open source software, available under a GPLv2 license. Sambamba can be downloaded and installed from http://www.open-bio.org/wiki/Sambamba. Sambamba v0.5.0 was released with doi:10.5281/zenodo.13200. Contact: j.c.p.prins@umcutrecht.nl |
format | Online Article Text |
id | pubmed-4765878 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47658782016-03-04 Sambamba: fast processing of NGS alignment formats Tarasov, Artem Vilella, Albert J. Cuppen, Edwin Nijman, Isaac J. Prins, Pjotr Bioinformatics Applications Notes Summary: Sambamba is a high-performance robust tool and library for working with SAM, BAM and CRAM sequence alignment files; the most common file formats for aligned next generation sequencing data. Sambamba is a faster alternative to samtools that exploits multi-core processing and dramatically reduces processing time. Sambamba is being adopted at sequencing centers, not only because of its speed, but also because of additional functionality, including coverage analysis and powerful filtering capability. Availability and implementation: Sambamba is free and open source software, available under a GPLv2 license. Sambamba can be downloaded and installed from http://www.open-bio.org/wiki/Sambamba. Sambamba v0.5.0 was released with doi:10.5281/zenodo.13200. Contact: j.c.p.prins@umcutrecht.nl Oxford University Press 2015-06-15 2015-02-19 /pmc/articles/PMC4765878/ /pubmed/25697820 http://dx.doi.org/10.1093/bioinformatics/btv098 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Tarasov, Artem Vilella, Albert J. Cuppen, Edwin Nijman, Isaac J. Prins, Pjotr Sambamba: fast processing of NGS alignment formats |
title | Sambamba: fast processing of NGS alignment formats |
title_full | Sambamba: fast processing of NGS alignment formats |
title_fullStr | Sambamba: fast processing of NGS alignment formats |
title_full_unstemmed | Sambamba: fast processing of NGS alignment formats |
title_short | Sambamba: fast processing of NGS alignment formats |
title_sort | sambamba: fast processing of ngs alignment formats |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4765878/ https://www.ncbi.nlm.nih.gov/pubmed/25697820 http://dx.doi.org/10.1093/bioinformatics/btv098 |
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