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      ADMIRE: analysis and visualization of differential methylation in genomic regions using the Infinium HumanMethylation450 Assay

      research-article
      Author(s): , , ,
      Publication date (Electronic):
      Journal: Epigenetics & Chromatin
      Publisher: BioMed Central

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          Abstract

          Background

          DNA methylation at cytosine nucleotides constitutes epigenetic gene regulation impacting cellular development and a wide range of diseases. Cytosine bases of the DNA are converted to 5-methylcytosine by the methyltransferase enzyme, acting as a reversible regulator of gene expression. Due to its outstanding importance in the epigenetic field, a number of lab techniques were developed to interrogate DNA methylation on a global range. Besides whole-genome bisulfite sequencing, the Infinium HumanMethylation450 Assay represents a versatile and cost-effective tool to investigate genome-wide changes of methylation patterns.

          Results

          Analysis of DNA Methylation In genomic REgions (ADMIRE) is an open source, semi-automatic analysis pipeline and visualization tool for Infinium HumanMethylation450 Assays with a special focus on ease of use. It features flexible experimental settings, quality control, automatic filtering, normalization, multiple testing, and differential analyses on arbitrary genomic regions. Publication-ready graphics, genome browser tracks, and table outputs include summary data and statistics, permitting instant comparison of methylation profiles between sample groups and the exploration of methylation patterns along the whole genome. ADMIREs statistical approach permits simultaneous large-scale analyses of hundreds of assays with little impact on algorithm runtimes.

          Conclusions

          The web-based version of ADMIRE provides a simple interface to researchers with limited programming skills, whereas the offline version is suitable for integration into custom pipelines. ADMIRE may be used via our freely available web service at https://bioinformatics.mpi-bn.mpg.de without any limitations concerning the size of a project. An offline version for local execution is available from our website or GitHub ( https://github.molgen.mpg.de/loosolab/admire).

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13072-015-0045-1) contains supplementary material, which is available to authorized users.

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          Most cited references21

          • Record: found
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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Jeremy Goecks, Anton Nekrutenko, James E. Taylor (2010)
          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
          Article 0 comments Cited 1421 times – based on 0 reviews     Review now
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            High density DNA methylation array with single CpG site resolution.

            Marina Bibikova, Bret Barnes, Chan Tsan … (2011)
            We have developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of the human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® Assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. We applied this technology to analyze DNA methylation in normal and tumor DNA samples and compared results with whole-genome bisulfite sequencing (WGBS) data obtained for the same samples. Highly comparable DNA methylation profiles were generated by the array and sequencing methods (average R2 of 0.95). The ability to determine genome-wide methylation patterns will rapidly advance methylation research. Copyright © 2011 Elsevier Inc. All rights reserved.
            Article 0 comments Cited 751 times – based on 0 reviews     Review now
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              Analysing and interpreting DNA methylation data.

              Christoph Bock (2012)
              DNA methylation is an epigenetic mark that has suspected regulatory roles in a broad range of biological processes and diseases. The technology is now available for studying DNA methylation genome-wide, at a high resolution and in a large number of samples. This Review discusses relevant concepts, computational methods and software tools for analysing and interpreting DNA methylation data. It focuses not only on the bioinformatic challenges of large epigenome-mapping projects and epigenome-wide association studies but also highlights software tools that make genome-wide DNA methylation mapping more accessible for laboratories with limited bioinformatics experience.
              Article 0 comments Cited 243 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Jens Preussner: jens.preussner@mpi-bn.mpg.de
                Julia Bayer: julia.bayer@mpi-bn.mpg.de
                Carsten Kuenne: carsten.kuenne@mpi-bn.mpg.de
                Mario Looso: mario.looso@mpi-bn.mpg.de
                Journal
                Journal ID (nlm-ta): Epigenetics Chromatin
                Journal ID (iso-abbrev): Epigenetics Chromatin
                Title: Epigenetics & Chromatin
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1756-8935
                Publication date (Electronic): 1 December 2015
                Publication date PMC-release: 1 December 2015
                Publication date Collection: 2015
                Volume: 8
                Electronic Location Identifier: 51
                Affiliations
                Bioinformatics Group, Max Planck Institute for Heart and Lung Research, Ludwigstrasse 43, 61231 Bad Nauheim, Germany
                Article
                Publisher ID: 45
                DOI: 10.1186/s13072-015-0045-1
                PMC ID: 4666223
                PubMed ID: 26628921
                SO-VID: b6181ffe-ca3d-4b02-9739-9b505a40e99c
                Copyright © © Preussner et al. 2015
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

                History
                Date received : 24 August 2015
                Date accepted : 17 November 2015
                Categories
                Subject: Methodology
                Custom metadata
                issue-copyright-statement © The Author(s) 2015

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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