A central question in the analysis of bisulfite sequencing data is to detect regions (collections of neighboring CpGs) with systematic differences between conditions, as compared to within-condition variability. These so-called Differentially Methylated Regions (DMRs) are thought to be more informative than single CpGs in terms of of biological function.
The package dmrseq provides a rigorous permutation-based approach to detect and perform inference for differential methylation by use of generalized least squares models that account for inter-individual and inter-CpG variability to generate region-level statistics that can be comparable across the genome. The framework performs well even on samples as small as two per group.
dmrseq is available on Bioconductor. You can install it with R version 3.5.0 or higher with the following commands:
See the vignette for information on how to use the package to perform typical methylation analysis workflows.
More details of the dmrseq framework can be found in the manuscript
Korthauer, K., Chakraborty, S., Benjamini, Y., and Irizarry, R.A. Detection and accurate False Discovery Rate control of differentially methylated regions from Whole Genome Bisulfite Sequencing Biostatistics, 2018 (in press). BioRxiv:10.1101/183210
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