R: Merge DMRs iteratively

mergeDMRsIteratively {DMRcaller}

R Documentation

Merge DMRs iteratively

Description

This function takes a list of DMRs and attempts to merge DMRs while keeping the new DMRs statistically significant.

Usage

mergeDMRsIteratively(DMRs, minGap, respectSigns = TRUE, methylationData1,
  methylationData2, context = "CG", minProportionDifference = 0.4,
  minReadsPerCytosine = 4, pValueThreshold = 0.01, test = "fisher",
  alternative = "two.sided", cores = 1)

Arguments

`DMRs`	the list of DMRs as a `GRanges` object; e.g. see `computeDMRs`
`minGap`	DMRs separated by a gap of at least `minGap` are not merged.
`respectSigns`	logical value indicating whether to respect the sign when joining DMRs.
`methylationData1`	the methylation data in condition 1 (see `methylationDataList`).
`methylationData2`	the methylation data in condition 2 (see `methylationDataList`).
`context`	the context in which the DMRs are computed (`"CG"`, `"CHG"` or `"CHH"`).
`minProportionDifference`	two adjacent DMRs are merged only if the difference in methylation proportion of the new DMR is higher than `minProportionDifference`.
`minReadsPerCytosine`	two adjacent DMRs are merged only if the number of reads per cytosine of the new DMR is higher than `minReadsPerCytosine`.
`pValueThreshold`	two adjacent DMRs are merged only if the p-value of the new DMR (see `test` below) is lower than `pValueThreshold`. Note that we adjust the p-values using the Benjamini and Hochberg's method to control the false discovery rate.
`test`	the statistical test used to call DMRs (`"fisher"` for Fisher's exact test or `"score"` for Score test).
`alternative`	indicates the alternative hypothesis and must be one of `"two.sided"`, `"greater"` or `"less"`.
`cores`	the number of cores used to compute the DMRs.

Value

the reduced list of DMRs as a GRanges object; e.g. see computeDMRs

Author(s)

Nicolae Radu Zabet

Examples

# load the methylation data
data(methylationDataList)

#load the DMRs in CG context they were computed with minGap = 200
data(DMRsNoiseFilterCG)


#merge the DMRs
DMRsNoiseFilterCGLarger <- mergeDMRsIteratively(DMRsNoiseFilterCG[1:100],
                           minGap = 500, respectSigns = TRUE,
                           methylationDataList[["WT"]],
                           methylationDataList[["met1-3"]],
                           context = "CG", minProportionDifference=0.4,
                           minReadsPerCytosine = 1, pValueThreshold=0.01,
                           test="score",alternative = "two.sided")


## Not run: 
#set genomic coordinates where to compute DMRs
regions <- GRanges(seqnames = Rle("Chr3"), ranges = IRanges(1,1E5))

# compute DMRs and remove gaps smaller than 200 bp
DMRsNoiseFilterCG200 <- computeDMRs(methylationDataList[["WT"]],
                       methylationDataList[["met1-3"]], regions = regions,
                       context = "CG", method = "noise_filter",
                       windowSize = 100, kernelFunction = "triangular",
                       test = "score", pValueThreshold = 0.01,
                       minCytosinesCount = 1, minProportionDifference = 0.4,
                       minGap = 200, minSize = 0, minReadsPerCytosine = 1,
                       cores = 1)

DMRsNoiseFilterCG0 <- computeDMRs(methylationDataList[["WT"]],
                       methylationDataList[["met1-3"]], regions = regions,
                       context = "CG", method = "noise_filter",
                       windowSize = 100, kernelFunction = "triangular",
                       test = "score", pValueThreshold = 0.01,
                       minCytosinesCount = 1, minProportionDifference = 0.4,
                       minGap = 0, minSize = 0, minReadsPerCytosine = 1,
                       cores = 1)
DMRsNoiseFilterCG0Merged200 <- mergeDMRsIteratively(DMRsNoiseFilterCG0,
                             minGap = 200, respectSigns = TRUE,
                             methylationDataList[["WT"]],
                             methylationDataList[["met1-3"]],
                             context = "CG", minProportionDifference=0.4,
                             minReadsPerCytosine = 1, pValueThreshold=0.01,
                             test="score",alternative = "two.sided")

#check that all newley computed DMRs are identical
print(all(DMRsNoiseFilterCG200 == DMRsNoiseFilterCG0Merged200))


## End(Not run)

[Package DMRcaller version 1.14.2 Index]