Identifying subpopulation methylation profiles from sequencing of heterogeneous samples with DXM

Changes in epigenetic marks, such as DNA methylation, in cancer subclones may increase their fitness, leading to cancer progression, treatment resistance, and worse prognosis. We have developed DXM, a novel computational method to identify subpopulation methylation events from bisulfite sequencing data of a heterogeneous sample DXM does not require prior knowledge of the number of cell types or what cell types to expect in the sample, and it outperforms existing methods. To further validate our method, we conducted genomic bisulfite sequencing on four primary DLBCL samples, obtaining data from >4.9 million CpGs at 50x average coverage. DXM predictions of subpopulation methylation profiles in these samples were confirmed in FACS-sorted CD4+ and CD19+ cells. Thus, we have developed a method, DXM, that can identify subpopulation methylation profiles in heterogeneous samples Overall design: Bisulfite Sequencing (Agilent Methyl-Seq) of four cryopreserved primary DLBCL samples