heatmapGenomewide: Genome wide heatmap of CNV-state

In ataudt/aneufinder: Analysis of Copy Number Variation in Single-Cell-Sequencing Data

Genome wide heatmap of CNV-state

Description

Plot a genome wide heatmap of copy number variation state. This heatmap is best plotted to file, because in most cases it will be too big for cleanly plotting it to screen.

Usage

heatmapGenomewide(hmms, ylabels = NULL, classes = NULL,
  classes.color = NULL, file = NULL,
  cluster = TRUE, plot.breakpoints = FALSE, hotspots = NULL,
  exclude.regions = NULL)

Arguments

hmms	A list of aneuHMM objects or a character vector with files that contain such objects.
ylabels	A vector with labels for the y-axis. The vector must have the same length as hmms. If NULL the IDs from the aneuHMM objects will be used.
classes	A character vector with the classification of the elements on the y-axis. The vector must have the same length as hmms.
classes.color	A (named) vector with colors that are used to distinguish classes. Names must correspond to the unique elements in classes.
file	A PDF file to which the heatmap will be plotted.
cluster	Either TRUE or FALSE, indicating whether the samples should be clustered by similarity in their CNV-state.
plot.breakpoints	Logical indicating whether breakpoints should be plotted.
hotspots	A GRanges-class object with coordinates of genomic hotspots (see hotspotter).
exclude.regions	A GRanges-class with regions that will be excluded from the computation of the clustering. This can be useful to exclude regions with artifacts.

Value

A ggplot object or NULL if a file was specified.

Examples

## Get results from a small-cell-lung-cancer
lung.folder <- system.file("extdata", "primary-lung", "hmms", package="AneuFinderData")
lung.files <- list.files(lung.folder, full.names=TRUE)
## Get results from the liver metastasis of the same patient
liver.folder <- system.file("extdata", "metastasis-liver", "hmms", package="AneuFinderData")
liver.files <- list.files(liver.folder, full.names=TRUE)
## Plot a clustered heatmap
classes <- c(rep('lung', length(lung.files)), rep('liver', length(liver.files)))
labels <- c(paste('lung',1:length(lung.files)), paste('liver',1:length(liver.files)))
heatmapGenomewide(c(lung.files, liver.files), ylabels=labels, classes=classes,
                 classes.color=c('blue','red'))

ataudt/aneufinder documentation built on April 18, 2023, 4:20 a.m.