TY - JOUR
T1 - COPAR
T2 - A ChIP-Seq Optimal Peak Analyzer
AU - Tang, Binhua
AU - Wang, Xihan
AU - Jin, Victor X.
N1 - Funding Information:
This work has been supported by the Natural Science Foundation of Jiangsu, China (BE2016655 and BK20161196), Fundamental Research Funds for China Central Universities (2016B08914), and Changzhou Science & Technology Program (CE20155050). This work made use of the resources supported by the NSFC-Guangdong Mutual Funds for Super Computing Program (2nd Phase) and the Open Cloud Consortium- (OCC-) sponsored project resource, supported in part by grants from Gordon and Betty Moore Foundation and the National Science Foundation (USA) and major contributions from OCC members.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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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U2 - 10.1155/2017/5346793
DO - 10.1155/2017/5346793
M3 - Article
C2 - 28357402
AN - SCOPUS:85015921256
VL - 2017
JO - BioMed Research International
JF - BioMed Research International
SN - 2314-6133
M1 - 5346793
ER -