Deconvolving the epigenome: analysis strategies for genome-wide studies
Seminar Room 1, Newton Institute
The emergence of economical high-throughput sequencing technologies has enabled unprecedented investigation of epigenetic marks on scales up to and including complete mammalian genomes. However, these technologies pose new challenges in terms of handling large data volumes, correcting for technical biases, and interpreting the results.
I discuss the challenges presented by these datasets, and describe Batman , a Bayesian Deconvolution method for the analysis and interpretion of methyl-DNA immunoprecipitation (MeDIP-seq) data, which we used to generate the first comprehensive DNA methylation profile for a mammalian genome. I will also talk about some outstanding issues, including the benefits of paired end sequencing approaches.
 Down TA, Rakyan VK, Turner DJ, Flicek P, Li J, Kulesha E, Graf S, Johnson N, Herrero J, Tomazou EM, Thorne NP, Backdahl L, Herberth M, Howe KL, Jackson DK, Miretti MM, Marioni JC, Birney E, Hubbard TJP, Durbin R, Tavare S, Beck S (2008) A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis. Nature Biotech 26:779-785