makeCpGregions {DMRScan} | R Documentation

## Cluster

### Description

Cluster CpGs together in regions based on proximity

### Usage

    makeCpGregions(observations, chr, pos, maxGap = 500, minCpG = 2)

### Arguments

`observations` | Vector of corresponding observed T-value for each CpG, must be ordered in the same way as chr and pos
`chr` | Vector of chromosome location for each CpG
`pos` | Vector giving base pair position for each CpG If unsorted, use order(chr,pos) to sort the genomic positions within each chromosome.
`maxGap` | Maximum allowed base pair gap within a cluster. Default is set to 500.
`minCpG` | Minimum number of CpGs allowed in each region to be considered. Default is set to at least 2 CpGs within each region.

### Value

The suplied observations ordered into into a GRangesList object. To be parsed further into `dmrscan`

### Examples

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

    ## Test for an association between phenotype and Methylation
    testStatistics <- 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
    pos<- data.frame(matrix(as.integer(unlist(strsplit(names(testStatistics),
    split="chr|[.]"))), ncol = 3, byrow = TRUE))[,-1]

    ## Set clustering features
    minCpG <- 3  ## Minimum number of CpGs in a tested cluster
    ## Maxium distance (in base-pairs) within a cluster before it is
    ## broken up into two seperate cluster
    maxGap <- 750
    regions <- makeCpGregions(observations = testStatistics, chr = pos[,1],
                                pos = pos[,2], maxGap = maxGap, minCpG = minCpG)

[Package DMRScan version 1.6.0 Index]