plotDecorate: Plot decorate analysis

In GabrielHoffman/decorate: Differential Epigenetic Coregulation Test

Plot decorate analysis

Description

Plot decorate analysis for clusters and correlations

Usage

plotDecorate(
  ensdb,
  treeList,
  treeListClusters,
  featurePositions,
  query,
  data,
  cols,
  showGenes = TRUE,
  splice_variants = FALSE,
  non_coding = FALSE,
  absCorr = FALSE,
  method.corr = c("pearson", "kendall", "spearman")
)

Arguments

ensdb	ENSEMBL database object like EnsDb.Hsapiens.v86
treeList	hierarchical clustering of each chromosome from runOrderedClusteringGenome()
treeListClusters	assign regions to clusters after cutting tree with createClusters()
featurePositions	GRanges object storing location of each feature
query	GRanges object indiecating region to plot
data	data to compute correlations stratified by testVariable
cols	array of color values
showGenes	plot genes
splice_variants	if TRUE, show multiple transcripts from the same gene
non_coding	if TRUE, also show non-coding genes
absCorr	show absolute correlations
method.corr	if data is specified, compute correlation using: "pearson", "kendall", "spearman"

Value

ggplot2 of cluster assignments and correlation between peaks

Examples

library(GenomicRanges)
library(EnsDb.Hsapiens.v86)

# load data
data('decorateData')

# load gene locations
ensdb = EnsDb.Hsapiens.v86

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

# Choose cutoffs and return clusters
treeListClusters = createClusters( treeList, method='meanClusterSize', meanClusterSize=30) 

# Plot correlations and clusters in region defined by query
query = range(simLocation)

plotDecorate( ensdb, treeList, treeListClusters, simLocation, query)

GabrielHoffman/decorate documentation built on May 23, 2023, 1:29 a.m.