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Title: Exemplary multiplex bisulfite amplicon data used to demonstrate the utility of Methpat.
Austin Authors: Wong, Nicholas C;Pope, Bernard J;Candiloro, Ida;Korbie, Darren;Trau, Matt;Wong, Stephen Q;Mikeska, Thomas;van Denderen, Bryce J W;Thompson, Erik W;Eggers, Stefanie;Doyle, Stephen R;Dobrovic, Alexander 
Affiliation: Translational Genomics and Epigenomics Laboratory, Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
Murdoch Childrens Research Institute, The Royal Children's Hospital, Parkville, Victoria, Australia
Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
Pacific Edge Biotechnology Ltd, Dunedin, Otago, New Zealand
Victorian Life Sciences Computation Initiative (VLSCI), The University of Melbourne, Parkville, Victoria, Australia
Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria, Australia
Department of Microbiology and Immunology, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC 3010 Australia
Department of Pathology, The University of Melbourne, Parkville, VIC 3052 Australia
Centre for Personalised NanoMedicine, Australian Institute of Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, Australia
School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072 Australia
Division of Cancer Research, Peter MacCallum Cancer Centre, East Melbourne, VIC 3002 Australia
Molecular Pathology Research and Development Laboratory, Department of Pathology, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia
Translational Research Laboratory, Division of Cancer Research, Peter MacCallum Cancer Centre, East Melbourne, VIC 3002 Australia
School of Cancer Medicine, La Trobe University, Bundoora, VIC 3084 Australia
St Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, 3065 Australia
Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
Department of Animal, Plant and Soil Sciences, La Trobe University, Bundoora, VIC 3086 Australia
Division of Cancer Medicine, La Trobe University, Bundoora, Victoria, Australia
Issue Date: 26-Nov-2015
Date: 2015-11-26
Publication information: GigaScience 2015; 4: 55
Abstract: DNA methylation is a complex epigenetic marker that can be analyzed using a wide variety of methods. Interpretation and visualization of DNA methylation data can mask complexity in terms of methylation status at each CpG site, cellular heterogeneity of samples and allelic DNA methylation patterns within a given DNA strand. Bisulfite sequencing is considered the gold standard, but visualization of massively parallel sequencing results remains a significant challenge. We created a program called Methpat that facilitates visualization and interpretation of bisulfite sequencing data generated by massively parallel sequencing. To demonstrate this, we performed multiplex PCR that targeted 48 regions of interest across 86 human samples. The regions selected included known gene promoters associated with cancer, repetitive elements, known imprinted regions and mitochondrial genomic sequences. We interrogated a range of samples including human cell lines, primary tumours and primary tissue samples. Methpat generates two forms of output: a tab-delimited text file for each sample that summarizes DNA methylation patterns and their read counts for each amplicon, and a HTML file that summarizes this data visually. Methpat can be used with publicly available whole genome bisulfite sequencing and reduced representation bisulfite sequencing datasets with sufficient read depths. Using Methpat, complex DNA methylation data derived from massively parallel sequencing can be summarized and visualized for biological interpretation. By accounting for allelic DNA methylation states and their abundance in a sample, Methpat can unmask the complexity of DNA methylation and yield further biological insight in existing datasets.
DOI: 10.1186/s13742-015-0098-x
Journal: GigaScience
PubMed URL: 26613017
ISSN: 2047-217X
Type: Journal Article
Subjects: Bisulfite sequencing
DNA methylation
Appears in Collections:Journal articles

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