heatmapGenomewide {AneuFinder} | R Documentation |
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.
heatmapGenomewide(hmms, ylabels = NULL, classes = NULL, reorder.by.class = TRUE, classes.color = NULL, file = NULL, cluster = TRUE, plot.breakpoints = FALSE, hotspots = NULL, exclude.regions = NULL)
hmms |
A list of |
ylabels |
A vector with labels for the y-axis. The vector must have the same length as |
classes |
A character vector with the classification of the elements on the y-axis. The vector must have the same length as |
reorder.by.class |
If |
classes.color |
A (named) vector with colors that are used to distinguish |
file |
A PDF file to which the heatmap will be plotted. |
cluster |
Either |
plot.breakpoints |
Logical indicating whether breakpoints should be plotted. |
hotspots |
A |
exclude.regions |
A |
A ggplot
object or NULL
if a file was specified.
## 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'))