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Cell Rep. 2016 Nov 15;17(8):2137-2150. doi: 10.1016/j.celrep.2016.10.059.

eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data.

Author information

1
UCL Cancer Institute, University College London, London WC1E 6BT, UK. Electronic address: c.breeze@ucl.ac.uk.
2
UCL Cancer Institute, University College London, London WC1E 6BT, UK.
3
Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081BT Amsterdam, the Netherlands.
4
UCL Cancer Institute, University College London, London WC1E 6BT, UK; Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK.
5
Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, E1 2AT London, UK.
6
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1HH, UK.
7
Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0QQ, UK.
8
Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK.
9
Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1HH, UK; Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0QQ, UK.
10
Département d'Informatique, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada.
11
Département d'Informatique, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada; Département de Biologie, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada; Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada.
12
Department of Human Genetics, McGill University, Montréal, QC H3G 1Y6, Canada; Génome Québec Innovation Center, Montréal, QC H3A 0G1, Canada.
13
Institute of Human Genetics, Christian Albrechts University, 24105 Kiel, Germany; Department of Pediatrics, Christian-Albrechts-University Kiel & University Hospital Schleswig-Holstein, 24105 Kiel, Germany.
14
Institute of Human Genetics, Christian Albrechts University, 24105 Kiel, Germany; Institute of Human Genetics, University of Ulm, Albert-Einstein-Allee 11, 89081 Ulm, Germany.
15
Department of Hematology, University of Groningen and University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, the Netherlands.
16
Department of Biochemistry, PMAS Arid Agriculture University Rawalpindi, 46300 Rawalpindi, Pakistan; Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, the Netherlands.
17
Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, 6500 HB Nijmegen, the Netherlands.
18
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
19
UCL Cancer Institute, University College London, London WC1E 6BT, UK. Electronic address: s.beck@ucl.ac.uk.

Abstract

Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell type-specific regulatory component of a set of EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to 20 publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology.

KEYWORDS:

DNase I hypersensitive sites; bioinformatics; epigenetics; epigenome-wide association study; histone marks

PMID:
27851974
PMCID:
PMC5120369
DOI:
10.1016/j.celrep.2016.10.059
[Indexed for MEDLINE]
Free PMC Article

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