MethPat: A tool for the analysis and visualisation of complex methylation patterns obtained by massively parallel sequencing

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Abstract

DNA methylation at a gene promoter region has the potential to regulate gene transcription. Patterns of methylation over multiple CpG sites in a region are often complex and cell type specific, with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). True representation of methylation patterns can only be fully characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount and complexity of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns.

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Wong, N. C., Pope, B. J., Candiloro, I. L., Korbie, D., Trau, M., Wong, S. Q., … Dobrovic, A. (2016). MethPat: A tool for the analysis and visualisation of complex methylation patterns obtained by massively parallel sequencing. BMC Bioinformatics, 17(1). https://doi.org/10.1186/s12859-016-0950-8

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