DMRScan_slidingWindow: DMR Scan function

In DMRScan: Detection of Differentially Methylated Regions

Description

DMR Scan function

Usage

dmrscan(observations, windowSize, windowThreshold = NULL, chr = NULL,
  pos = NULL, maxGap = 500, ...)

Arguments

observations	An object of either; GRangesList made by makeCpGregions, a vector of the test statistic, a GRanges object, or a "minfi" object (soon to be supported).
windowSize	A sequence of windowSizes for the slidingWindow. Must be an integer vector, with equal length as the number of windows.
windowThreshold	Optional argument with corresponding cut-off for each window. Will be estimated if not supplied.
chr	A vector of chromosomal position. Only used when the observations vector is a matrix of test statistic.
pos	A vector of genomic coordinates for the CpGs to match the chr argument
maxGap	The maximum allowed gap between two CpGs within the same region.
...	Optional arguments to be passed to estimateThreshold, if no grid is specified.

Value

An object of type GRanges with significantly differentially

Examples

## methylation data from chromosome 22 
data(DMRScan.methylationData)
## phenotype (end-point for methylation data)

data(DMRScan.phenotypes) 

## Test for an association between phenotype and methylation
test.statistics <- apply(DMRScan.methylationData,1,function(x,y)
  summary(glm(y ~ x, family = binomial(link = "logit")))$coefficients[2,3],
                                                   y = DMRScan.phenotypes)
## Set chromosomal position to each test-statistic
positions <- data.frame(matrix(as.integer(unlist(strsplit(names(test.statistics), 
                               split="chr|[.]"))), ncol = 3, byrow = TRUE))[,-1]
## Set clustering features 
min.cpg <- 4  ## Minimum number of CpGs in a tested cluster
## Maximum distance (in base-pairs) within a cluster 
## before it is broken up into two separate cluster 
max.gap <- 750  

## Identify all clusters, and generate a list for each cluster
regions <- makeCpGregions(observations = test.statistics, 
                          chr = positions[,1], pos = positions[,2], 
                          maxGap = max.gap, minCpG = min.cpg)
## Number of CpGs in the slidingWindows, can be either a single number 
## or a sequence of windowSizes
windowSizes <- 3:7 
nCpG        <- sum(sapply(regions,length)) ## Number of CpGs to be tested

# Estimate the windowThreshold, based on the number of CpGs and windowSizes
windowThresholds <- estimateWindowThreshold(nProbe = nCpG, 
               windowSize = windowSizes, method = "sampling", mcmc = 10000)
## Run the slidingWindow
DMRScanResults   <- dmrscan(observations = regions, 
                            windowSize = windowSizes, 
                            windowThreshold = windowThresholds)
## Print the result
print(DMRScanResults)

DMRScan documentation built on Nov. 8, 2020, 8:10 p.m.