dmrFinder: Finds differentially methylated regions for whole genome...
In bsseq: Analyze, manage and store bisulfite sequencing data

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

Finds differentially methylated regions for whole genome bisulfite sequencing data. Essentially identifies regions of the genome where all methylation loci have an associated t-statistic that is beyond a (low, high) cutoff.

1 2	dmrFinder(bstat, cutoff = NULL, qcutoff = c(0.025, 0.975), maxGap=300, stat = "tstat.corrected", verbose = TRUE)

`bstat`	An object of class `BSseqStat` or `BSseqTstat`.
`cutoff`	The cutoff of the t-statistics. This should be a vector of length two giving the (low, high) cutoff. If `NULL`, see `qcutoff`.
`qcutoff`	In case `cutoff` is `NULL`, compute the cutoff using these quantiles of the t-statistic.
`maxGap`	If two methylation loci are separated by this distance, break a possible DMR. This guarantees that the return DMRs have CpGs that are this distance from each other.
`stat`	Which statistic should be used?
`verbose`	Should the function be verbose?

The workhorse function is BSmooth.tstat which sets up a t-statistic for a comparison between two groups.

Note that post-processing of these DMRs are likely to be necessary, filtering for example for length (or number of loci).

A data.frame with columns

`start,end,width,chr`	genomic locations and width.
`n`	The number of methylation loci.
`invdensity`	Average length per loci.
`group1.mean`	The mean methylation level across samples and loci in 'group1'.
`group2.mean`	The mean methylation level across samples and loci in 'group2'.
`meanDiff`	The mean difference in methylation level; the difference between `group1.mean` and `group2.mean`.
`idxStart, idxEnd, cluster`	Internal use.
`areaStat`	The 'area' of the t-statistic; equal to the sum of the t-statistics for the individual methylation loci.
`direction`	either ‘hyper’ or ‘hypo’.
`areaStat.corrected`	Only present if `column = "tstat.corrected"`, contains the area of the corrected t-statistics.

Kasper Daniel Hansen khansen@jhsph.edu.

KD Hansen, B Langmead, and RA Irizarry. BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biology (2012) 13:R83. doi:10.1186/gb-2012-13-10-r83.

BSmooth.tstat for the function constructing the input object, and BSseqTstat for its class. In the example below, we use BS.cancer.ex.tstat as the actual input object. Also see the package vignette(s) for a detailed example.

if(require(bsseqData)) {
  dmrs0 <- dmrFinder(BS.cancer.ex.tstat, cutoff = c(-4.6, 4.6), verbose = TRUE)
  dmrs <- subset(dmrs0, abs(meanDiff) > 0.1 & n >= 3)
}

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