An R package for identification of differentially methylated regions (DMRs) from high density chip, for example Illumina 450K, data.
The seqlm method works in three stages.
Stage 1: The genome is divided into smaller pieces based on a genomic distance cutoff.
Stage 2: In each piece probes are segmented into regions that have approximately constant difference between the groups of interest. Example of the segmentation and its process is shown in schema.
- In sliding windows with variable sizes we fit a linear models to the data.
- For each model we record the description length - the amount of bits needed to describe the data using the model
- Using dynamic programming we find the segmentation that minimizes total description length
Stage 3: We assess the relevance of each segment, by using a mixed model where the classes are a fixed effect and a sample is a random effect. This model takes into account the repeated nature of the consecutive methylation measurements. The segments are ordered by their significance.
The most convenient way to install the package is by using the devtools package.
library(devtools)
install_github("seqlm", "raivokolde")To start using the package just load it as any other package.
library(seqlm)For running the code one has to have three objects:
- matrix with methylation values;
- vector specifying the classes of columns (only two-class case is supported currently);
- location information about the methylation probes in GRanges format (example can be downloaded from here).