COPAR: A ChIP-Seq Optimal Peak Analyzer. Biomed Res Int 2017;2017:5346793
Date
03/31/2017Pubmed ID
28357402Pubmed Central ID
PMC5357551DOI
10.1155/2017/5346793Scopus ID
2-s2.0-85015921256 (requires institutional sign-in at Scopus site)Abstract
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.
Author List
Tang B, Wang X, Jin VXAuthor
Victor X. Jin PhD Professor in the Institute for Health and Equity department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
GenomeGenomics
High-Throughput Nucleotide Sequencing
Humans
Sequence Analysis, DNA
Software