Abstract
Motivation: The rapid development of high-throughput sequencing technologies has enabled epigeneticists to quantify DNA methylation on a massive scale. Progressive increase in sequencing capacity present challenges in terms of processing analysis and the interpretation of the large amount of data; investigating differential methylation between genome-scale data from multiple samples highlights this challenge. Results: We have developed a differential methylation analysis package (DMAP) to generate coverage-filtered reference methylomes and to identify differentially methylated regions across multiple samples from reduced representation bisulphite sequencing and whole genome bisulphite sequencing experiments. We introduce a novel fragment-based approach for investigating DNA methylation patterns for reduced representation bisulphite sequencing data. Further, DMAP provides the identity of gene and CpG features and distances to the differentially methylated regions in a format that is easily analyzed with limited bioinformatics knowledge. Availability and implementation: The software has been implemented in C and has been written to ensure portability between different platforms. The source code and documentation is freely available (DMAP: as compressed TAR archive folder) fromhttp://biochem. otago. ac. nz/research/databases-software/. Two test datasets are also available for download from the Web site. Test dataset 1 contains reads from chromosome 1 of a patient and a control, which is used for comparative analysis in the current article. Test dataset 2 contains reads from a part of chromosome 21 of three disease and three control samples for testing the operation of DMAP, especially for the analysis of variance. Example commands for the analyses are included.