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      COCOA: coordinate covariation analysis of epigenetic heterogeneity

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          Abstract

          A key challenge in epigenetics is to determine the biological significance of epigenetic variation among individuals. We present Coordinate Covariation Analysis (COCOA), a computational framework that uses covariation of epigenetic signals across individuals and a database of region sets to annotate epigenetic heterogeneity. COCOA is the first such tool for DNA methylation data and can also analyze any epigenetic signal with genomic coordinates. We demonstrate COCOA’s utility by analyzing DNA methylation, ATAC-seq, and multi-omic data in supervised and unsupervised analyses, showing that COCOA provides new understanding of inter-sample epigenetic variation. COCOA is available on Bioconductor ( http://bioconductor.org/packages/COCOA).

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

          Yoav Benjamini, Yosef Hochberg (1995)
          Article 0 comments Cited 25156 times – based on 0 reviews     Review now
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            JASPAR: an open-access database for eukaryotic transcription factor binding profiles.

            Albin Sandelin, Wynand Alkema, Pär G. Engström … (2004)
            The analysis of regulatory regions in genome sequences is strongly based on the detection of potential transcription factor binding sites. The preferred models for representation of transcription factor binding specificity have been termed position-specific scoring matrices. JASPAR is an open-access database of annotated, high-quality, matrix-based transcription factor binding site profiles for multicellular eukaryotes. The profiles were derived exclusively from sets of nucleotide sequences experimentally demonstrated to bind transcription factors. The database is complemented by a web interface for browsing, searching and subset selection, an online sequence analysis utility and a suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. JASPAR is available at http://jaspar. cgb.ki.se.
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              Targeting EZH2 in cancer.

              Kimberly H Kim, Charles Roberts (2016)
              Recent genomic studies have resulted in an emerging understanding of the role of chromatin regulators in the development of cancer. EZH2, a histone methyl transferase subunit of a Polycomb repressor complex, is recurrently mutated in several forms of cancer and is highly expressed in numerous others. Notably, both gain-of-function and loss-of-function mutations occur in cancers but are associated with distinct cancer types. Here we review the spectrum of EZH2-associated mutations, discuss the mechanisms underlying EZH2 function, and synthesize a unifying perspective that the promotion of cancer arises from disruption of the role of EZH2 as a master regulator of transcription. We further discuss EZH2 inhibitors that are now showing early signs of promise in clinical trials and also additional strategies to combat roles of EZH2 in cancer.
              Article 0 comments Cited 620 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Nathan C. Sheffield:
                ORCID: http://orcid.org/0000-0001-5643-4068
                nsheffield@virginia.edu
                Journal
                Journal ID (nlm-ta): Genome Biol
                Journal ID (iso-abbrev): Genome Biol
                Title: Genome Biology
                Publisher: BioMed Central (London )
                ISSN (Print): 1474-7596
                ISSN (Electronic): 1474-760X
                Publication date (Electronic): 7 September 2020
                Publication date PMC-release: 7 September 2020
                Publication date Collection: 2020
                Volume: 21
                Electronic Location Identifier: 240
                Affiliations
                [1 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Department of Biomedical Engineering, , University of Virginia, ; Charlottesville, VA USA
                [2 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Center for Public Health Genomics, , University of Virginia, ; Charlottesville, VA USA
                [3 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Department of Biochemistry and Molecular Genetics, , University of Virginia, ; Charlottesville, VA USA
                [4 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, Department of Medicine, , University of Virginia, ; Charlottesville, VA USA
                [5 ]GRID grid.27755.32, ISNI 0000 0000 9136 933X, University of Virginia Cancer Center, ; Charlottesville, USA
                Author information
                http://orcid.org/0000-0001-5643-4068
                Article
                Publisher ID: 2139
                DOI: 10.1186/s13059-020-02139-4
                PMC ID: 7487606
                PubMed ID: 32894181
                SO-VID: 20e7fe0a-5740-4915-8fa4-65f458e40a1e
                Copyright © © The Author(s) 2020
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 11 March 2020
                Date accepted : 7 August 2020
                Funding
                Funded by: National Institute of General Medical Sciences (US)
                Award ID: GM128636
                Award Recipient :
                Categories
                Subject: Method
                Custom metadata
                issue-copyright-statement © The Author(s) 2020

                ScienceOpen disciplines: Genetics
                Keywords: epigenetics,dna methylation,chromatin accessibility,principal component analysis,dimensionality reduction,data integration,cancer,ezh2,multi-omics
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: epigenetics, dna methylation, chromatin accessibility, principal component analysis, dimensionality reduction, data integration, cancer, ezh2, multi-omics

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