Journal
BIOINFORMATICS
Volume 25, Issue 15, Pages 1952-1958Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btp340
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Funding
- University Facilitating Fund
- National Science Foundation [DMR0313129]
- Intramural Research Program for the National Heart Lung and blood Institute
- National Institute of Health
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Motivation: Chromatin states are the key to gene regulation and cell identity. Chromatin immunoprecipitation (ChIP) coupled with high-throughput sequencing (ChIP-Seq) is increasingly being used to map epigenetic states across genomes of diverse species. Chromatin modi. cation profiles are frequently noisy and diffuse, spanning regions ranging from several nucleosomes to large domains of multiple genes. Much of the early work on the identification of ChIP-enriched regions for ChIP-Seq data has focused on identifying localized regions, such as transcription factor binding sites. Bioinformatic tools to identify diffuse domains of ChIP-enriched regions have been lacking. Results: Based on the biological observation that histone modi. cations tend to cluster to form domains, we present a method that identifies spatial clusters of signals unlikely to appear by chance. This method pools together enrichment information from neighboring nucleosomes to increase sensitivity and specificity. By using genomic-scale analysis, as well as the examination of loci with validated epigenetic states, we demonstrate that this method outperforms existing methods in the identification of ChIP-enriched signals for histone modi. cation profiles. We demonstrate the application of this unbiased method in important issues in ChIP-Seq data analysis, such as data normalization for quantitative comparison of levels of epigenetic modi. cations across cell types and growth conditions.
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