dmpFinder: Find differentially methylated positions
In minfi: Analyze Illumina Infinium DNA methylation arrays

Description Usage Arguments Details Value Author(s) See Also Examples

Identify CpGs where methylation is associated with a continuous or categorical phenotype.

1 2	dmpFinder(dat, pheno, type = c("categorical", "continuous"), qCutoff = 1, shrinkVar = FALSE)

`dat`	A `MethylSet` or a `matrix`.
`pheno`	The phenotype to be tested for association with methylation.
`type`	Is the phenotype '‘continuous’ or ‘categorical’?
`qCutoff`	DMPs with an FDR q-value greater than this will not be returned.
`shrinkVar`	Should variance shrinkage be used? See details.

This function tests each genomic position for association between methylation and a phenotype. Continuous phenotypes are tested with linear regression, while an F-test is used for categorical phenotypes.

Variance shrinkage (shrinkVar=TRUE) is recommended when sample sizes are small (<10). The sample variances are squeezed by computing empirical Bayes posterior means using the limma package.

A table with one row per CpG.

Martin Aryee aryee@jhu.edu.

squeezeVar and the limma package in general.

if (require(minfiData)) {

grp <- pData(MsetEx)$Sample_Group
MsetExSmall <- MsetEx[1:1e4,] # To speed up the example
M <- getM(MsetExSmall, type = "beta", betaThreshold = 0.001)
dmp <- dmpFinder(M, pheno=grp, type="categorical")
sum(dmp$qval < 0.05, na.rm=TRUE)
head(dmp)

}