plotHeatmap: Heatmap plot

In shahcompbio/signals: Single Cell Genomes with Allele Specificity

Heatmap plot

Description

Plot a heatmap where rows are cells, columns are genome coordinates and colours map to (allele-specific) copy-number states

Usage

plotHeatmap(
  cn,
  tree = NULL,
  clusters = NULL,
  annotations = NULL,
  normalize_ploidy = FALSE,
  normalize_tree = FALSE,
  branch_length = 1,
  spacer_cols = 20,
  plottree = TRUE,
  plotcol = "state",
  reorderclusters = FALSE,
  pctcells = 0.05,
  library_mapping = NULL,
  clone_pal = NULL,
  sample_label_idx = 1,
  fillna = TRUE,
  frequencycutoff = 2,
  frequency_bar_width = 0.5,
  maxf = NULL,
  plotfrequency = FALSE,
  frequency_height = 1.4,
  show_legend = TRUE,
  show_library_label = TRUE,
  show_clone_label = TRUE,
  show_clone_text = TRUE,
  widenarm = FALSE,
  umapmetric = "euclidean",
  chrlabels = TRUE,
  labeladjust = -5,
  SV = NULL,
  seed = NULL,
  nticks = 4,
  Mb = TRUE,
  fillgenome = FALSE,
  annotation_height = NULL,
  annofontsize = 10,
  na_col = "white",
  linkheight = 2.5,
  newlegendname = NULL,
  str_to_remove = NULL,
  maxCNcol = 11,
  anno_width = 0.4,
  rasterquality = 15,
  tree_width = 4,
  ladderize = TRUE,
  ...
)

Arguments

cn	Either a hscn object or a single cell allele specific copy number dataframe with the following columns: 'cell_id', 'chr', 'start', 'end', 'state', 'copy'
tree	Tree in newick format to plot alongside the heatmap, default = NULL
clusters	data.frame assigning cells to clusters, needs the following columns 'cell_id', 'clone_id' default = NULL
annotations	Optional dataframe containing cell_id column and additional annotation columns
normalize_ploidy	Normalize ploidy of all cells to 2
normalize_tree	default = FALSE
branch_length	scales branch lengths to this size, default = 2
spacer_cols	number of empty columns between chromosomes, default = 20
plottree	Binary value of whether to plot tree or not, default = TRUE
plotcol	Which column to colour the heatmap by, should be one of "state", "state_BAF", "state_phase", "state_AS", "state_min", "copy", "BAF", "A", "B"
reorderclusters	Reorder the cells according to cluster if no tree is specified
pctcells	Minimum size of cluster in terms of perecentage of cells in umap clustering
library_mapping	Named vector mapping library names to labels for legend
clone_pal	pallette to colour clusters by
sample_label_idx	default = 1
fillna	Smooth over NA values, default = TRUE
frequencycutoff	default = 2
frequency_bar_width	Width of bars for frequency track, default = 0.5
maxf	Max frequency when plotting the frequency track, default = NULL infers this from the data
plotfrequency	Plot the frequency track of gains and losses across the genome
frequency_height	height of the frequency track if using, default = 1.4
show_legend	plot legend or not, boolean
show_library_label	show library label or not, boolean
show_clone_label	show clone label or not, boolean
show_clone_text	Show small inset labels next to clone/cluster annotation
widenarm	Widen the copy number data table to include all bins
umapmetric	metric to use in umap dimensionality reduction if no clusters are specified
chrlabels	include chromosome labels or not, boolean
labeladjust
SV	sv data frame
seed	seed for UMAP
nticks	number of ticks in x-axis label when plotting a single chromosome
Mb	Use Mb ticks when plotting single chromosome
fillgenome	fill in any missing bins and add NA to centromeric regions
annotation_height	Height of the annotations
annofontsize	Font size to use for annotations, default = 10
na_col	colour of NA values
linkheight	height of x-axis ticks
newlegendname	overwrite default legend name
str_to_remove	string to remove from cell_id's when plotting labels
maxCNcol	max value for color scale when plotting raw data
anno_width	width of left annotations
rasterquality	default = 15
tree_width	Width of phylogenetic tree, default = 4
ladderize	ladderize the tree, default = TRUE, same as default in ggtree If clusters are set to NULL then the function will compute clusters using UMAP and HDBSCAN.

Examples

## Not run: 
data("haplotypes")
data("CNbins")
haplotypes <- format_haplotypes_dlp(haplotypes, CNbins)
hscn <- callHaplotypeSpecificCN(CNbins, haplotypes, likelihood = "binomial")
plotHeatmap(hscn)

## End(Not run)

shahcompbio/signals documentation built on Jan. 11, 2025, 2:20 a.m.