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Bioinformatics. 2012 Jun 15;28(12):i163-71. doi: 10.1093/bioinformatics/bts231.

Detection of allele-specific methylation through a generalized heterogeneous epigenome model.

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Department of Computer Science and Engineering, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.



High-throughput sequencing has made it possible to sequence DNA methylation of a whole genome at the single-base resolution. A sample, however, may contain a number of distinct methylation patterns. For instance, cells of different types and in different developmental stages may have different methylation patterns. Alleles may be differentially methylated, which may partially explain that the large portions of epigenomes from single cell types are partially methylated, and may have major effects on transcriptional output. Approaches relying on DNA sequence polymorphism to identify individual patterns from a mixture of heterogeneous epigenomes are insufficient as methylcytosines occur at a much higher density than SNPs.


We have developed a mixture model-based approach for resolving distinct epigenomes from a heterogeneous sample. In particular, the model is applied to the detection of allele-specific methylation (ASM). The methods are tested on a synthetic methylome and applied to an Arabidopsis single root cell methylome.

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