The Epigenome Center at Baylor College of Medicine participates in the NIH Epigenomics Roadmap Project. The aim of the NIH Epigenomics Roadmap project is to understand the variation of epigenomes (methylation status, histone marks, chromatin accessibility) across major tissue types and experimentally relevant cell lines and to detect and interpret epigenomic variation due to a selected set of developmental, physiological, and disease processes. The project will produce a Human Epigenome Atlas. The Atlas contains epigenomic maps of major tissue types and experimentally relevant cell lines.
The Center's broad aim is to understand the variation of epigenomes (methylation status, histone marks, chromatin accessibility) across major human tissue types and experimentally relevant human cell lines and to detect and interpret epigenomic variation due to a selected set of developmental, physiological, and disease processes.
The Epigenome Center is the Epigenomics Data Analysis and Coordination Center (EDACC) for the NIH Roadmap Epigenomic Project. The role of the EDACC is to provide data analysis and coordination for all Reference Epigenome Mapping Centers.
Genboree is a turnkey software system for genomic research. The Epigenomics Data Analysis and Coordination Center and a number of collaborative epigenomic projects use Genboree as their core informatic infrastructure.
The Human Epigenome Atlas contains epigenomic maps of major tissue types and experimentally relevant cell lines.
The International Human Epigenome Consortium: A Blueprint for Scientific Collaboration and Discovery
Cell. doi: 10.1016/j.cell.2016.11.007 (2016)
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Epigenomic Deconvolution of Breast Tumors Reveals Metabolic Coupling between Constituent Cell Types
Cell Rep. doi: 10.1016/j.celrep.2016.10.057 (2016)
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Nat. Commun. 6:6370 doi: 10.1038/ncomms7370 (2015)
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Integrative analysis of 111 reference human epigenomes
Nature doi: 10.1038/nature14248 (2015)
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BMC Bioinformatics. 2014;15 Suppl 7:S2. doi: 10.1186/1471-2105-15-S7-S2. Epub 2014 May 28.
PMID: 25080362
Comparison and quantitative verification of mapping algorithms for whole-genome bisulfite sequencing
Nucleic Acids Res. 2014 Apr;42(6):e43. doi: 10.1093/nar/gkt1325. Epub 2014 Jan 3.
PMID: 24391148
Recommendations for the design and analysis of epigenome-wide association studies
Nat Methods. 2013 Oct;10(10):949-55. doi: 10.1038/nmeth.2632. Review.
PMID: 24076989
PLoS Genet. 2013;9(2):e1003333. doi: 10.1371/journal.pgen.1003333. Epub 2013 Feb 28. No abstract available.
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Spark: a navigational paradigm for genomic data exploration
Genome Res. 2012 Nov;22(11):2262-9. doi: 10.1101/gr.140665.112. Epub 2012 Sep 7.
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Genome Biol. 2012 Jun 15;13(6):R43. doi: 10.1186/gb-2012-13-6-r43.
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PLoS Genet. 2012;8(5):e1002692. doi: 10.1371/journal.pgen.1002692. Epub 2012 May 17.
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Emerging patterns of epigenomic variation
Trends in Genetics, 2011 Jun;27(6):242-50
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Putting epigenome comparison into practice
Nat Biotechnol., 2010 Oct;28(10):1053-6
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The NIH Roadmap Epigenomics Mapping Consortium
Nat Biotechnol., 2010 Oct;28(10):1045-8
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Nat Biotechnol., 2010 Oct;28(10):1097-105
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