ArticleBioinformatics (Oxford, England)2017
EpiCompare: an online tool to define and explore genomic regions with tissue or cell type-specific epigenomic features.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- chromIDEAS reveals epigenetic dynamics via multi-dimensional clustering of chromatin states.Nucleic acids research · 2026Article
- UALCAN Mobile, an app for cancer proteogenomic data analysis.Research square · 2025Article
- UALCAN Mobile, an app for cancer proteogenomic data analysis.bioRxiv : the preprint server for biology · 2025Article
- Epilogos: information-theoretic navigation of multi-tissue functional genomic annotations.bioRxiv : the preprint server for biology · 2025Article
- Robust chromatin state annotation.Genome research · 2024Article
- A framework for group-wise summarization and comparison of chromatin state annotations.Bioinformatics (Oxford, England) · 2023Article
- Computational methods to explore chromatin state dynamics.Briefings in bioinformatics · 2022Review
- Epigenomic analysis of Parkinson's disease neurons identifies Tet2 loss as neuroprotective.Nature neuroscience · 2020Article
- Hemispheric asymmetry in the human brain and in Parkinson's disease is linked to divergent epigenetic patterns in neurons.Genome biology · 2020Article
- EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences.Nucleic acids research · 2019Article
- The NIH Common Fund/Roadmap Epigenomics Program: Successes of a comprehensive consortium.Science advances · 2019Review
- Epigenetic dysregulation of enhancers in neurons is associated with Alzheimer's disease pathology and cognitive symptoms.Nature communications · 2019Article
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Authors and funding
2 authors.
Funding
Abstract
motivationThe 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.
resultsAn 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. AVAILABILITY AND IMPLEMENTATION: EpiCompare is freely available on the web at http://epigenome.wustl.edu/EpiCompare/. CONTACT: twang@genetics.wustl.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.