Scatter plot of all pairs of variables stratified by test variable
Source:R/plotCorrPairs.R
plotScatterPairs.Rd
Scatter plot of all pairs of variables stratified by test variable
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
- size
size of points
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, 30) )
#> Method:meanClusterSize
# get peak ID's from chr1, cluster 1
peakIDs = getFeaturesInCluster( treeListClusters, "chr20", 2, "30")
# plot comparison of correlation matrices for peaks in peakIDs
# where data is subset by metadata$Disease
plotScatterPairs( simData, peakIDs, metadata$Disease) + ggtitle("chr20: cluster 1")
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#> `geom_smooth()` using formula = 'y ~ x'
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#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
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#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
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#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
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#> `geom_smooth()` using formula = 'y ~ x'
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