DML {sesame} | R Documentation

## Test differential methylation on each locus

### Description

The function takes a beta value matrix with probes on the rows and samples on the columns. It also takes a sample information data frame (meta) and formula for testing. The function outputs a list of coefficient tables for each factor tested.

### Usage

    DML(betas, fm, meta = NULL, mc.cores = 1)

### Arguments

`betas` | beta values, matrix or SummarizedExperiment rows are probes and columns are samples.
`fm` | formula
`meta` | 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. When the betas argument is a SummarizedExperiment object, this is ignored. colData(betas) will be used instead.
`mc.cores` | number of cores for parallel processing

### Value

a list of test summaries, summary.lm objects

### Examples

    sesameDataCache("HM450") # in case not done yet
    data <- sesameDataGet('HM450.76.TCGA.matched')
    smry <- DML(data$betas[1:1000,], ~type, meta=data$sampleInfo)

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

[Package sesame version 1.12.9 Index]