The Genomedata format for storing large-scale functional genomics data

Summary: We present a format for efficient storage of multiple tracks of numeric data anchored to a genome. The format allows fast random access to hundreds of gigabytes of data, while retaining a small disk space footprint. We have also developed utilities to load data into this format. We show tha...

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Detalles Bibliográficos
Autores principales: Hoffman, Michael M., Buske, Orion J., Noble, William Stafford
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2872006/
https://www.ncbi.nlm.nih.gov/pubmed/20435580
http://dx.doi.org/10.1093/bioinformatics/btq164
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author Hoffman, Michael M.
Buske, Orion J.
Noble, William Stafford
author_facet Hoffman, Michael M.
Buske, Orion J.
Noble, William Stafford
author_sort Hoffman, Michael M.
collection PubMed
description Summary: We present a format for efficient storage of multiple tracks of numeric data anchored to a genome. The format allows fast random access to hundreds of gigabytes of data, while retaining a small disk space footprint. We have also developed utilities to load data into this format. We show that retrieving data from this format is more than 2900 times faster than a naive approach using wiggle files. Availability and Implementation: Reference implementation in Python and C components available at http://noble.gs.washington.edu/proj/genomedata/ under the GNU General Public License. Contact: william-noble@uw.edu
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spelling pubmed-28720062010-05-24 The Genomedata format for storing large-scale functional genomics data Hoffman, Michael M. Buske, Orion J. Noble, William Stafford Bioinformatics Applications Note Summary: We present a format for efficient storage of multiple tracks of numeric data anchored to a genome. The format allows fast random access to hundreds of gigabytes of data, while retaining a small disk space footprint. We have also developed utilities to load data into this format. We show that retrieving data from this format is more than 2900 times faster than a naive approach using wiggle files. Availability and Implementation: Reference implementation in Python and C components available at http://noble.gs.washington.edu/proj/genomedata/ under the GNU General Public License. Contact: william-noble@uw.edu Oxford University Press 2010-06-01 2010-04-29 /pmc/articles/PMC2872006/ /pubmed/20435580 http://dx.doi.org/10.1093/bioinformatics/btq164 Text en © The Author 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Hoffman, Michael M.
Buske, Orion J.
Noble, William Stafford
The Genomedata format for storing large-scale functional genomics data
title The Genomedata format for storing large-scale functional genomics data
title_full The Genomedata format for storing large-scale functional genomics data
title_fullStr The Genomedata format for storing large-scale functional genomics data
title_full_unstemmed The Genomedata format for storing large-scale functional genomics data
title_short The Genomedata format for storing large-scale functional genomics data
title_sort genomedata format for storing large-scale functional genomics data
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2872006/
https://www.ncbi.nlm.nih.gov/pubmed/20435580
http://dx.doi.org/10.1093/bioinformatics/btq164
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