COPAR: A ChIP-Seq Optimal Peak Analyzer

Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for...

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Detalles Bibliográficos
Autores principales: Tang, Binhua, Wang, Xihan, Jin, Victor X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5357551/
https://www.ncbi.nlm.nih.gov/pubmed/28357402
http://dx.doi.org/10.1155/2017/5346793
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author Tang, Binhua
Wang, Xihan
Jin, Victor X.
author_facet Tang, Binhua
Wang, Xihan
Jin, Victor X.
author_sort Tang, Binhua
collection PubMed
description Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for ChIP-sequencing profiles. We developed open-sourced COPAR, a user-friendly package, to statistically investigate, quantify, and visualize the optimal peak alignment and inherent genomic features using ChIP-seq data from NGS experiments. It provides a versatile perspective for biologists to perform quality-check for high-throughput experiments and optimize their experiment design. The package COPAR can process mapped ChIP-seq read file in BED format and output statistically sound results for multiple high-throughput experiments. Together with three public ChIP-seq data sets verified with the developed package, we have deposited COPAR on GitHub under a GNU GPL license.
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spelling pubmed-53575512017-03-29 COPAR: A ChIP-Seq Optimal Peak Analyzer Tang, Binhua Wang, Xihan Jin, Victor X. Biomed Res Int Research Article Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for ChIP-sequencing profiles. We developed open-sourced COPAR, a user-friendly package, to statistically investigate, quantify, and visualize the optimal peak alignment and inherent genomic features using ChIP-seq data from NGS experiments. It provides a versatile perspective for biologists to perform quality-check for high-throughput experiments and optimize their experiment design. The package COPAR can process mapped ChIP-seq read file in BED format and output statistically sound results for multiple high-throughput experiments. Together with three public ChIP-seq data sets verified with the developed package, we have deposited COPAR on GitHub under a GNU GPL license. Hindawi 2017 2017-03-05 /pmc/articles/PMC5357551/ /pubmed/28357402 http://dx.doi.org/10.1155/2017/5346793 Text en Copyright © 2017 Binhua Tang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Tang, Binhua
Wang, Xihan
Jin, Victor X.
COPAR: A ChIP-Seq Optimal Peak Analyzer
title COPAR: A ChIP-Seq Optimal Peak Analyzer
title_full COPAR: A ChIP-Seq Optimal Peak Analyzer
title_fullStr COPAR: A ChIP-Seq Optimal Peak Analyzer
title_full_unstemmed COPAR: A ChIP-Seq Optimal Peak Analyzer
title_short COPAR: A ChIP-Seq Optimal Peak Analyzer
title_sort copar: a chip-seq optimal peak analyzer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5357551/
https://www.ncbi.nlm.nih.gov/pubmed/28357402
http://dx.doi.org/10.1155/2017/5346793
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