scbp: Boilerplate functions for single cell rna-seq analysis

plot_heatmap

R Documentation

Plot heatmap per cluster/cell-type

Description

Plot heatmap per cluster/cell-type

Usage

plot_heatmap(
  obj,
  features,
  group,
  annotations = group,
  average = FALSE,
  slot = "scale.data",
  max_disp = 2.5,
  col_palettes = NULL,
  default_discrete_pal = discrete_palette_default,
  default_continuous_pal_fxn = viridis::inferno(256),
  hmap_options = NULL
)

Arguments

`obj`	Seurat object
`features`	features to plot as rows
`group`	column from meta data to use to group cells across columns
`annotations`	additional meta.data columns to add as column annotations supplied as a character vector, defaults to display just group
`average`	if TRUE, return average values per group rather than display all cells
`slot`	data slot to retrive values defaults to scale.data
`max_disp`	max/min value to display (2.5), only applied for scale.data
`col_palettes`	list of alternative palettes to use for each annotation + group variable supplied.
`default_discrete_pal`	defatul discrete palette, defaults to scbp::discrete_palette_default,
`hmap_options`	named list of options that are passed to ComplexHeatmap::Heatmap
`normalize_cell_counts`	if TRUE, downsample cell counts to minimum cell count per group
`default_continuous_pal`	default continuous color palette, defaults to viridis::inferno(256)

Examples

pbmc_small <- get_example_data()
plot_heatmap(pbmc_small,
             features = rownames(pbmc_small@assays$RNA@scale.data),
             group = "letter.idents",
             annotations = colnames(pbmc_small@meta.data))

rnabioco/scbp documentation built on July 7, 2023, 10:10 p.m.