Description Usage Arguments Value Examples
View source: R/makeCpGranges.R
Cluster CpGs together in genes based on annotation
| 1 | makeCpGgenes(observations, chr, pos, gene, minCpG = 2)
 | 
| 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. | 
The suplied observations ordered into into a list, with one entry for each CpG region.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | 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)
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