DMR {sesame} | R Documentation

## Find Differentially Methylated Region (DMR)

### Description

This subroutine uses Euclidean distance to group CpGs and then combine p-values for each segment. The function performs DML test first if cf is NULL. It groups the probe testing results into differential methylated regions in a coefficient table with additional columns designating the segment ID and statistical significance (P-value) testing the segment.

### Usage

    DMR(
      betas,
      smry,
      contrast,
      platform = NULL,
      refversion = NULL,
      dist.cutoff = NULL,
      seg.per.locus = 0.5
    )

### Arguments

`betas` | beta values for distance calculation
`smry` | DML
`contrast` | the pair-wise comparison or contrast check colnames(attr(smry, "model.matrix")) if uncertain
`platform` | EPIC, HM450, MM285, ...
`refversion` | hg38, hg19, mm10, ...
`dist.cutoff` | distance cutoff (default to use dist.cutoff.quantile)
`seg.per.locus` | number of segments per locus higher value leads to more segments

### Value

coefficient table with segment ID and segment P-value each row is a locus, multiple loci may share a segment ID if they are merged to the same segment. Records are ordered by Seg_Est.

### Examples

    sesameDataCache("HM450") # in case not done yet

    data <- sesameDataGet('HM450.76.TCGA.matched')
    smry <- DML(data$betas[1:1000,], ~type, meta=data$sampleInfo)
    colnames(attr(smry, "model.matrix")) # pick a contrast from here
    merged_segs = DMR(data$betas[1:1000,], smry, "typeTumour")

    # release memory for Windows package builder
    rm(list=ls(env=sesameData:::cacheEnv), envir=sesameData:::cacheEnv)
    gc()

[Package sesame version 1.12.9 Index]