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EpiCompare: an online tool to define and explore genomic regions with tissue or cell type-specific epigenomic features

Author:
He, Yu, Wang, Ting
Source:
Bioinformatics 2017 v.33 no.20 pp. 3268-3275
ISSN:
1460-2059
Subject:
algorithms, bioinformatics, computer software, data collection, epigenetics, genome, genomics, humans, prediction, regulatory sequences, tissues
Abstract:
The Human Reference Epigenome Map, generated by the Roadmap Epigenomics Consortium, contains thousands of genome-wide epigenomic datasets that describe epigenomes of a variety of different human tissue and cell types. This map has allowed investigators to obtain a much deeper and more comprehensive view of our regulatory genome, e.g. defining regulatory elements including all promoters and enhancers for a given tissue or cell type. An outstanding task is to combine and compare different epigenomes in order to identify regions with epigenomic features specific to certain types of tissues or cells, e.g. lineage-specific regulatory elements. Currently available tools do not directly address this question. This need motivated us to develop a tool that allows investigators to easily identify regions with epigenetic features unique to specific epigenomes that they choose, making detection of common regulatory elements and/or cell type-specific regulatory elements an interactive and dynamic experience. An online tool EpiCompare was developed to assist investigators in exploring the specificity of epigenomic features across selected tissue and cell types. Investigators can design their test by choosing different combinations of epigenomes, and choosing different classification algorithms provided by our tool. EpiCompare will then identify regions with specified epigenomic features, and provide a quality assessment of the predictions. Investigators can interact with EpiCompare by investigating Roadmap Epigenomics data, or uploading their own data for comparison. We demonstrate that by using specific combinations of epigenomes we can detect developmental lineage-specific enhancers. Finally, prediction results can be readily visualized and further explored in the WashU Epigenome Browser. EpiCompare is freely available on the web at http://epigenome.wustl.edu/EpiCompare/. twang@genetics.wustl.edu Supplementary data are available at Bioinformatics online.
Agid:
6248907