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PeakRanger: A cloud-enabled peak caller for ChIP-seq data

BACKGROUND: Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor b...

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Detalles Bibliográficos
Autores principales: Feng, Xin, Grossman, Robert, Stein, Lincoln
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3103446/
https://www.ncbi.nlm.nih.gov/pubmed/21554709
http://dx.doi.org/10.1186/1471-2105-12-139
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author Feng, Xin
Grossman, Robert
Stein, Lincoln
author_facet Feng, Xin
Grossman, Robert
Stein, Lincoln
author_sort Feng, Xin
collection PubMed
description BACKGROUND: Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks. RESULTS: In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project. CONCLUSIONS: Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project: http://www.modencode.org/software/ranger/
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spelling pubmed-31034462011-05-28 PeakRanger: A cloud-enabled peak caller for ChIP-seq data Feng, Xin Grossman, Robert Stein, Lincoln BMC Bioinformatics Software BACKGROUND: Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks; few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks. RESULTS: In this paper, we introduce PeakRanger, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized. In addition, PeakRanger can be run in a parallel cloud computing environment to obtain extremely high performance on very large data sets. We present a series of benchmarks to evaluate PeakRanger against 10 other peak callers, and demonstrate the performance of PeakRanger on both real and synthetic data sets. We also present real world usages of PeakRanger, including peak-calling in the modENCODE project. CONCLUSIONS: Compared to other peak callers tested, PeakRanger offers improved resolution in distinguishing extremely closely-spaced peaks. PeakRanger has above-average spatial accuracy in terms of identifying the precise location of binding events. PeakRanger also has excellent sensitivity and specificity in all benchmarks evaluated. In addition, PeakRanger offers significant improvements in run time when running on a single processor system, and very marked improvements when allowed to take advantage of the MapReduce parallel environment offered by a cloud computing resource. PeakRanger can be downloaded at the official site of modENCODE project: http://www.modencode.org/software/ranger/ BioMed Central 2011-05-09 /pmc/articles/PMC3103446/ /pubmed/21554709 http://dx.doi.org/10.1186/1471-2105-12-139 Text en Copyright © 2011 Feng et al; licensee BioMed Central Ltd. https://creativecommons.org/licenses/by/2.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Feng, Xin
Grossman, Robert
Stein, Lincoln
PeakRanger: A cloud-enabled peak caller for ChIP-seq data
title PeakRanger: A cloud-enabled peak caller for ChIP-seq data
title_full PeakRanger: A cloud-enabled peak caller for ChIP-seq data
title_fullStr PeakRanger: A cloud-enabled peak caller for ChIP-seq data
title_full_unstemmed PeakRanger: A cloud-enabled peak caller for ChIP-seq data
title_short PeakRanger: A cloud-enabled peak caller for ChIP-seq data
title_sort peakranger: a cloud-enabled peak caller for chip-seq data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3103446/
https://www.ncbi.nlm.nih.gov/pubmed/21554709
http://dx.doi.org/10.1186/1471-2105-12-139
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