DMR {sesame} | R Documentation |
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.
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"), ...)
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 |
coefficient table with segment ID and segment P-value
data <- sesameDataGet('HM450.76.TCGA.matched') cf <- DMR(data$betas, data$sampleInfo, ~type)