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Updated: Jan 8, 2026

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues
Published on: April 5, 2018
Towards personalized epigenomics: learning shared chromatin landscapes and joint de-noising of histone modification
Tanmayee Narendra1, Giovanni Visonà2, Crhistian de Jesus Cardona1
1Division of Computational Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee DD15EH, United Kingdom.
Abstract:
Epigenetic mechanisms enable cellular differentiation and the maintenance of distinct cell types. They enable rapid responses to external signals through changes in gene regulation and their registration over longer time spans. Consequently, the chromatin landscape, which is the overall organization and biochemical state of chromatin, exhibits both cell-type and individual specificity and contributes to phenotypic diversity. Genomic distributions of chromatin features are typically measured using chromatin immunoprecipitation sequencing and related methods. However, these measurements are subject to substantial biases introduced by the chromatin landscape itself. Here, we introduce DecoDen, which uses measurements of several different histone modifications, to simultaneously learn shared chromatin landscapes while de-biasing individual measurement tracks. We demonstrate DecoDen's effectiveness on an integrative analysis of histone modification patterns across multiple tissues in personal epigenomes. DecoDen is available at https://github.com/ntanmayee/decoden.
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