findDMRs: Aggregates CpG sites to DMRs
In BiSeq: Processing and analyzing bisulfite sequencing data

Description Usage Arguments Value Author(s) See Also Examples

This function aggregates CpG sites to DMRs on the basis of their P values.

1	findDMRs(test.out, alpha, max.dist, diff.dir)

`test.out`	An object returned by `betaRegression`.
`alpha`	OPTIONAL. A DMR contains CpG sites with P values smaller or equal than `alpha`.
`max.dist`	Numeric. The maximum distance between two P values smaller than `alpha` in a DMR. Should be the same as `grid.dist` in `predictMeth`.
`diff.dir`	Logical. Should DMRs be seperated if the direction of methylation differences changes? If `TRUE` (default), than resulting DMRs will consist of sites which are all hypomethylated, or hypermethylated respectively.

A GRanges object storing the start and end positions of the DMRs with information in metadata columns:

`median.p`	median of P values
`median.meth.group1`	median of modeled methylation level of group1.
`median.meth.group1`	median of modeled methylation level of group2.
`median.meth.diff`	median of difference of modeled methylation levels of group1 and group2.

Katja Hebestreit

predictMeth, betaRegression

## Variogram under Null hypothesis (for resampled data):
data(vario)

plot(vario$variogram$v)
vario.sm <- smoothVariogram(vario, sill=0.9)

# auxiliary object to get the pValsList for the test
# results of interest:
data(betaResults)
vario.aux <- makeVariogram(betaResults, make.variogram=FALSE)

# Replace the pValsList slot:
vario.sm$pValsList <- vario.aux$pValsList

## vario.sm contains the smoothed variogram under the Null hypothesis as
## well as the p Values that the group has an effect on DNA methylation.

locCor <- estLocCor(vario.sm)

clusters.rej <- testClusters(locCor, FDR.cluster = 0.1)

clusters.trimmed <- trimClusters(clusters.rej, FDR.loc = 0.05)

DMRs <- findDMRs(clusters.trimmed, max.dist=100, diff.dir=TRUE)