Combined plot of correlation matricies from cases and controls
Arguments
- epiSignal
matrix or EList of epigentic signal. Rows are features and columns are samples
- peakIDs
feature names to extract from rows of epiSignal
- testVariable
factor indicating two subsets of the samples to compare
- cols
array of color values
- size
size of text
- absCorr
show absolute correlations
Examples
library(GenomicRanges)
data('decorateData')
# Evaluate hierarchical clsutering
treeList = runOrderedClusteringGenome( simData, simLocation )
#>
Evaluating:chr20
#>
# Choose cutoffs and return clusters
treeListClusters = createClusters( treeList, method = "meanClusterSize", meanClusterSize=c( 10, 20) )
#> Method:meanClusterSize
# Simulate variable to split dataset by
set.seed(1)
metadata = data.frame( Disease = factor(sample(0:1, ncol(simData), replace=TRUE)))
# get peak ID's from chr1, cluster 1
peakIDs = getFeaturesInCluster( treeListClusters, "chr1", 1, "10")
# plot comparison of correlation matrices for peaks in peakIDs
# where data is subset by metadata$Disease
plotCompareCorr( simData, peakIDs, metadata$Disease) + ggtitle("chr1: cluster 1")