heatmapGenomewide: Genome wide heatmap of CNV-state
In AneuFinder: Analysis of Copy Number Variation in Single-Cell-Sequencing Data

Description Usage Arguments Value Examples

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 `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`.
`reorder.by.class`	If `TRUE`, the dendrogram will be reordered to display similar classes next to each other.
`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.

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'))