makeCpGgenes {DMRScan} | R Documentation

## Cluster

### Description

Cluster CpGs together in genes based on annotation

### Usage

    makeCpGgenes(observations, chr, pos, gene, 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.
`gene` | A vector asigning each probe to a gene.
`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 list, with one entry for each CpG region.

### 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
    gene     <- sample(paste("Gene",1:100,sep=""),
                               length(testStatistics),replace=TRUE)
    regions  <- makeCpGgenes(observations = testStatistics,
                             chr = pos[,1], pos = pos[,2],
                             gene = gene, minCpG = minCpG)

[Package DMRScan version 1.6.0 Index]