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,
      sample.data = NULL,
      formula = NULL,
      cf = NULL,
      dist.cutoff = NULL,
      seg.per.locus = 0.5,
      platform = c("EPIC", "HM450"),
      refversion = c("hg38", "hg19"),
      ...
    )

### Arguments

`betas` | beta values for distance calculation
`sample.data` | data frame for sample information, column names are predictor variables (e.g., sex, age, treatment, tumor/normal etc) and are referenced in formula. Rows are samples.
`formula` | formula
`cf` | coefficient table from diffMeth, when NULL will be computed from beta. If cf is given, sample.data and formula are ignored.
`dist.cutoff` | distance cutoff (default to use dist.cutoff.quantile)
`seg.per.locus` | number of segments per locus higher value leads to more segments
`platform` | EPIC or HM450
`refversion` | hg38 or hg19
`...` | additional parameters to DML

### Value

coefficient table with segment ID and segment P-value

### Examples

    data <- sesameDataGet('HM450.76.TCGA.matched')
    cf <- DMR(data$betas, data$sampleInfo, ~type)

[Package sesame version 1.6.0 Index]