WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis

Motivation: Using high-throughput sequencing, researchers are now generating hundreds of whole-genome assays to measure various features such as transcription factor binding, histone marks, DNA methylation or RNA transcription. Displaying so much data generally leads to a confusing accumulation of p...

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Autores principales: Zerbino, Daniel R., Johnson, Nathan, Juettemann, Thomas, Wilder, Steven P., Flicek, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967112/
https://www.ncbi.nlm.nih.gov/pubmed/24363377
http://dx.doi.org/10.1093/bioinformatics/btt737
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author Zerbino, Daniel R.
Johnson, Nathan
Juettemann, Thomas
Wilder, Steven P.
Flicek, Paul
author_facet Zerbino, Daniel R.
Johnson, Nathan
Juettemann, Thomas
Wilder, Steven P.
Flicek, Paul
author_sort Zerbino, Daniel R.
collection PubMed
description Motivation: Using high-throughput sequencing, researchers are now generating hundreds of whole-genome assays to measure various features such as transcription factor binding, histone marks, DNA methylation or RNA transcription. Displaying so much data generally leads to a confusing accumulation of plots. We describe here a multithreaded library that computes statistics on large numbers of datasets (Wiggle, BigWig, Bed, BigBed and BAM), generating statistical summaries within minutes with limited memory requirements, whether on the whole genome or on selected regions. Availability and Implementation: The code is freely available under Apache 2.0 license at www.github.com/Ensembl/Wiggletools Contact: zerbino@ebi.ac.uk or flicek@ebi.ac.uk
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spelling pubmed-39671122014-04-18 WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis Zerbino, Daniel R. Johnson, Nathan Juettemann, Thomas Wilder, Steven P. Flicek, Paul Bioinformatics Applications Notes Motivation: Using high-throughput sequencing, researchers are now generating hundreds of whole-genome assays to measure various features such as transcription factor binding, histone marks, DNA methylation or RNA transcription. Displaying so much data generally leads to a confusing accumulation of plots. We describe here a multithreaded library that computes statistics on large numbers of datasets (Wiggle, BigWig, Bed, BigBed and BAM), generating statistical summaries within minutes with limited memory requirements, whether on the whole genome or on selected regions. Availability and Implementation: The code is freely available under Apache 2.0 license at www.github.com/Ensembl/Wiggletools Contact: zerbino@ebi.ac.uk or flicek@ebi.ac.uk Oxford University Press 2014-04-01 2013-12-19 /pmc/articles/PMC3967112/ /pubmed/24363377 http://dx.doi.org/10.1093/bioinformatics/btt737 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Zerbino, Daniel R.
Johnson, Nathan
Juettemann, Thomas
Wilder, Steven P.
Flicek, Paul
WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis
title WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis
title_full WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis
title_fullStr WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis
title_full_unstemmed WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis
title_short WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis
title_sort wiggletools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967112/
https://www.ncbi.nlm.nih.gov/pubmed/24363377
http://dx.doi.org/10.1093/bioinformatics/btt737
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