metilene: fast and sensitive calling of differentially methylated regions from bisulfite sequencing data
- Frank Jühling1,2,7,
- Helene Kretzmer1,2,7,
- Stephan H. Bernhart1,2,
- Christian Otto1,2,
- Peter F. Stadler2,3,4,5,6 and
- Steve Hoffmann1,2
- 1Transcriptome Bioinformatics Group, LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, 04107 Leipzig, Germany;
- 2Interdisciplinary Center for Bioinformatics and Bioinformatics Group, Faculty of Computer Science, University of Leipzig, 04107 Leipzig, Germany;
- 3RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology - IZI, 04103 Leipzig, Germany;
- 4Santa Fe Institute, Santa Fe, New Mexico 87501, USA;
- 5Department of Theoretical Chemistry, University of Vienna, 1090 Vienna, Austria;
- 6Max Planck Institute for Mathematics in Sciences, 04103 Leipzig, Germany
- Corresponding author: steve{at}bioinf.uni-leipzig.de
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↵7 These authors contributed equally to this work.
Abstract
The detection of differentially methylated regions (DMRs) is a necessary prerequisite for characterizing different epigenetic states. We present a novel program, metilene, to identify DMRs within whole-genome and targeted data with unrivaled specificity and sensitivity. A binary segmentation algorithm combined with a two-dimensional statistical test allows the detection of DMRs in large methylation experiments with multiple groups of samples in minutes rather than days using off-the-shelf hardware. metilene outperforms other state-of-the-art tools for low coverage data and can estimate missing data. Hence, metilene is a versatile tool to study the effect of epigenetic modifications in differentiation/development, tumorigenesis, and systems biology on a global, genome-wide level. Whether in the framework of international consortia with dozens of samples per group, or even without biological replicates, it produces highly significant and reliable results.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.196394.115.
- Received July 1, 2015.
- Accepted November 25, 2015.
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