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FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology

Summary: Next-generation sequencing can provide insight into protein–DNA association events on a genome-wide scale, and is being applied in an increasing number of applications in genomics and meta-genomics research. However, few software applications are available for interpreting these experiments...

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Autores principales: Fejes, Anthony P., Robertson, Gordon, Bilenky, Mikhail, Varhol, Richard, Bainbridge, Matthew, Jones, Steven J. M.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2638869/
https://www.ncbi.nlm.nih.gov/pubmed/18599518
http://dx.doi.org/10.1093/bioinformatics/btn305
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author Fejes, Anthony P.
Robertson, Gordon
Bilenky, Mikhail
Varhol, Richard
Bainbridge, Matthew
Jones, Steven J. M.
author_facet Fejes, Anthony P.
Robertson, Gordon
Bilenky, Mikhail
Varhol, Richard
Bainbridge, Matthew
Jones, Steven J. M.
author_sort Fejes, Anthony P.
collection PubMed
description Summary: Next-generation sequencing can provide insight into protein–DNA association events on a genome-wide scale, and is being applied in an increasing number of applications in genomics and meta-genomics research. However, few software applications are available for interpreting these experiments. We present here an efficient application for use with chromatin-immunoprecipitation (ChIP-Seq) experimental data that includes novel functionality for identifying areas of gene enrichment and transcription factor binding site locations, as well as for estimating DNA fragment size distributions in enriched areas. The FindPeaks application can generate UCSC compatible custom ‘WIG’ track files from aligned-read files for short-read sequencing technology. The software application can be executed on any platform capable of running a Java Runtime Environment. Memory requirements are proportional to the number of sequencing reads analyzed; typically 4 GB permits processing of up to 40 million reads. Availability: The FindPeaks 3.1 package and manual, containing algorithm descriptions, usage instructions and examples, are available at http://www.bcgsc.ca/platform/bioinfo/software/findpeaks Source files for FindPeaks 3.1 are available for academic use. Contact: afejes@bcgsc.ca
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spelling pubmed-26388692009-02-25 FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology Fejes, Anthony P. Robertson, Gordon Bilenky, Mikhail Varhol, Richard Bainbridge, Matthew Jones, Steven J. M. Bioinformatics Applications Note Summary: Next-generation sequencing can provide insight into protein–DNA association events on a genome-wide scale, and is being applied in an increasing number of applications in genomics and meta-genomics research. However, few software applications are available for interpreting these experiments. We present here an efficient application for use with chromatin-immunoprecipitation (ChIP-Seq) experimental data that includes novel functionality for identifying areas of gene enrichment and transcription factor binding site locations, as well as for estimating DNA fragment size distributions in enriched areas. The FindPeaks application can generate UCSC compatible custom ‘WIG’ track files from aligned-read files for short-read sequencing technology. The software application can be executed on any platform capable of running a Java Runtime Environment. Memory requirements are proportional to the number of sequencing reads analyzed; typically 4 GB permits processing of up to 40 million reads. Availability: The FindPeaks 3.1 package and manual, containing algorithm descriptions, usage instructions and examples, are available at http://www.bcgsc.ca/platform/bioinfo/software/findpeaks Source files for FindPeaks 3.1 are available for academic use. Contact: afejes@bcgsc.ca Oxford University Press 2008-08-01 2008-07-03 /pmc/articles/PMC2638869/ /pubmed/18599518 http://dx.doi.org/10.1093/bioinformatics/btn305 Text en © 2008 The Author(s) 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/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Fejes, Anthony P.
Robertson, Gordon
Bilenky, Mikhail
Varhol, Richard
Bainbridge, Matthew
Jones, Steven J. M.
FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
title FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
title_full FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
title_fullStr FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
title_full_unstemmed FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
title_short FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
title_sort findpeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2638869/
https://www.ncbi.nlm.nih.gov/pubmed/18599518
http://dx.doi.org/10.1093/bioinformatics/btn305
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