Motivation: Chromatin accessibility plays a key role in epigenetic regulation of gene activation and silencing. Open chromatin regions allow regulatory elements such as transcription factors and polymerases to bind for gene expression while closed chromatin regions prevent the activity of transcriptional machinery. Recently, Methyltransferase Accessibility Protocol for individual templates-Bisulfite Genome Sequencing (MAPit-BGS) and nucleosome occupancy and methylome sequencing (NOMe-seq) have been developed for simultaneously profiling chromatin accessibility and DNA methylation on single molecules. Therefore, there is a great demand in developing computational methods to identify chromatin accessibility from MAPit-BGS and NOMe-seq. Results: In this article, we present CAME (Chromatin Accessibility and Methylation), a seed-extension based approach that identifies chromatin accessibility from NOMe-seq. The efficiency and effectiveness of CAME were demonstrated through comparisons with other existing techniques on both simulated and real data, and the results show that our method not only can precisely identify chromatin accessibility but also outperforms other methods. Availability and Implementation: CAME is implemented in java and the program is freely available online at http://sourceforge.net/projects/came/. Contacts: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

It is well known that cancer cells are diverse and heterogeneous among patients, and that this heterogeneity makes cancer diagnosis and cure difficult. Intra-tumoral heterogeneity has very recently become important because a small proportion of drug-resistant or tumor-initiating cells can ultimately determine a patient's outcome. In this study, we propose new approaches to use variance tests, including the Lepage test, to identify inter-patient cancer heterogeneity, as well as multinomial logistic regression to identify intra-patient cancer heterogeneity, i.e., different epiallele composition. We conduct experiments to show the performance of the proposed approaches.