Tumor purity deconvolution software tools | Bisulfite sequencing data analysis
In recent years, whole genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) have been increasingly used to profile the DNA methylation patterns between tumors and their normal counterparts, where differential methylated regions not only serve as important cancer biomarkers and therapeutic targets, but also provide insights to the mechanism of tumorigenesis and progression.
Uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. MethylPurify can identify differentially methylated regions (DMRs) from individual tumor methylome samples, without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. From patient data, MethylPurify gave satisfactory DMR calls from tumor methylome samples alone, and revealed potential missed DMRs by tumor to normal comparison due to tumor heterogeneity.
Uses sequencing reads from high-throughput sequencing of bisulfite-converted DNA to reconstruct heterogeneous cell populations by assembling cell-specific methylation patterns. methylFlow is based on the solution of a specific class of minimum cost network flow problems. Our method allows researchers to probe intra-cellular epigenomic heterogeneity from a standard sequencing experiment of pooled cells. This work opens new avenues in the analysis of epigenomes as statistical extensions to our work here can start addressing questions of differential presence of cell-specific methylation patterns across phenotypes of interest, and begin to understand specific changes in the epigenomic complexity of cell communities.