plotCompareCorr: Plot two correlation matrices together
In GabrielHoffman/decorate: Differential Epigenetic Coregulation Test

Description Usage Arguments Value Examples

Combined plot of correlation matricies from cases and controls

plotCompareCorr(
  epiSignal,
  peakIDs,
  testVariable,
  cols,
  size = 5,
  absCorr = FALSE
)

`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

ggplot2 of combined correlation matrix

library(GenomicRanges)

data('decorateData')

# Evaluate hierarchical clsutering
treeList = runOrderedClusteringGenome( simData, simLocation ) 

# Choose cutoffs and return clusters
treeListClusters = createClusters( treeList, method = "meanClusterSize", meanClusterSize=c( 10, 20) )

# 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")