title: COPAR: A ChIP-Seq Optimal Peak Analyzer.
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.
authors.affiliation: Epigenetics & Function Group, School of Internet of Things, Hohai University, Jiangsu 213022, China; School of Public Health & Biostatistics, Shanghai Jiao Tong University, Shanghai 200025, China.
authors.forename: Binhua
authors.identifier: 0000-0003-4744-5835
authors.initials: B
authors.lastname: Tang
authors.affiliation: Epigenetics & Function Group, School of Internet of Things, Hohai University, Jiangsu 213022, China.
authors.forename: Xihan
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Molecular Medicine & Biostatistics, University of Texas Health Science Center, San Antonio, TX 78249, USA.
authors.forename: Victor X
authors.initials: VX
authors.lastname: Jin
mesh_terms: D016678:Genome / Q000235:genetics*; D023281:Genomics; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software