View source: R/plotCorrPairs.R

plotScatterPairs | R Documentation |

Scatter plot of all pairs of variables stratified by test variable

```
plotScatterPairs(epiSignal, peakIDs, testVariable, size = 1)
```

`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 |

ggplot2 of combined pairwise scatter plots

```
library(GenomicRanges)
data('decorateData')
# Evaluate hierarchical clsutering
treeList = runOrderedClusteringGenome( simData, simLocation )
# Choose cutoffs and return clusters
treeListClusters = createClusters( treeList, method = "meanClusterSize", meanClusterSize=c(10, 30) )
# 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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