plotDecorate: Plot decorate analysis

Description Usage Arguments Value Examples

View source: R/plots.R

Description

Plot decorate analysis for clusters and correlations

Usage

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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

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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 Aug. 8, 2019, 1:48 p.m.