DML: Test differential methylation on each locus

In sesame: Tools For Analyzing Illumina Infinium DNA Methylation Arrays

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 (sample.data) and formula for testing. The function outputs a list of coefficient tables for each factor tested.

Usage

DML(
  betas,
  sample.data,
  formula,
  se.lb = 0.06,
  balanced = FALSE,
  cf.test = NULL
)

Arguments

betas	beta values
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
se.lb	lower bound to standard error of slope, lower this to get more difference of small effect size.
balanced	whether design is balanced or not. default to FALSE, when unbalanced will use Welch's method to estimate standard error. balance=TRUE is faster.
cf.test	factors to test (default to all factors in formula except intercept). Use "all" for all factors.

Value

cf - a list of coefficient tables for each factor

Examples

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

sesame documentation built on Nov. 15, 2020, 2:08 a.m.