do_ExpressionHeatmap: Create heatmaps of averaged expression by groups.

View source: R/do_ExpressionHeatmap.R

do_ExpressionHeatmapR Documentation

Create heatmaps of averaged expression by groups.

Description

This function generates a heatmap with averaged expression values by the unique groups of the metadata variables provided by the user.

Usage

do_ExpressionHeatmap(
  sample,
  features,
  group.by = NULL,
  assay = NULL,
  cluster = TRUE,
  features.order = NULL,
  groups.order = NULL,
  slot = "data",
  legend.title = "Avg. Expression",
  na.value = "grey75",
  legend.position = "bottom",
  legend.width = 1,
  legend.length = 20,
  legend.framewidth = 0.5,
  legend.tickwidth = 0.5,
  legend.framecolor = "grey50",
  legend.tickcolor = "white",
  legend.type = "colorbar",
  font.size = 14,
  font.type = "sans",
  axis.text.x.angle = 45,
  enforce_symmetry = FALSE,
  min.cutoff = NA,
  max.cutoff = NA,
  diverging.palette = "RdBu",
  diverging.direction = -1,
  sequential.palette = "YlGnBu",
  sequential.direction = 1,
  number.breaks = 5,
  use_viridis = FALSE,
  viridis.palette = "G",
  viridis.direction = -1,
  flip = FALSE,
  grid.color = "white",
  border.color = "black",
  plot.title.face = "bold",
  plot.subtitle.face = "plain",
  plot.caption.face = "italic",
  axis.title.face = "bold",
  axis.text.face = "plain",
  legend.title.face = "bold",
  legend.text.face = "plain"
)

Arguments

sample

Seurat | A Seurat object, generated by CreateSeuratObject.

features

character | Features to represent.

group.by

character | Metadata variable to group the output by. Has to be a character of factor column.

assay

character | Assay to use. Defaults to the current assay.

cluster

logical | Whether to perform clustering of rows and columns.

features.order

character | Should the gene sets be ordered in a specific way? Provide it as a vector of characters with the same names as the names of the gene sets.

groups.order

named_list | Should the groups in theheatmaps be ordered in a specific way? Provide it as a named list (as many lists as values in group.by) with the order for each of the elements in the groups.

slot

character | Data slot to use. Only one of: counts, data, scale.data. Defaults to "data".

legend.title

character | Title for the legend.

na.value

character | Color value for NA.

legend.position

character | Position of the legend in the plot. One of:

  • top: Top of the figure.

  • bottom: Bottom of the figure.

  • left: Left of the figure.

  • right: Right of the figure.

  • none: No legend is displayed.

legend.length, legend.width

numeric | Length and width of the legend. Will adjust automatically depending on legend side.

legend.framewidth, legend.tickwidth

numeric | Width of the lines of the box in the legend.

legend.framecolor

character | Color of the lines of the box in the legend.

legend.tickcolor

character | Color of the ticks of the box in the legend.

legend.type

character | Type of legend to display. One of:

  • normal: Default legend displayed by ggplot2.

  • colorbar: Redefined colorbar legend, using guide_colorbar.

font.size

numeric | Overall font size of the plot. All plot elements will have a size relationship with this font size.

font.type

character | Base font family for the plot. One of:

  • mono: Mono spaced font.

  • serif: Serif font family.

  • sans: Default font family.

axis.text.x.angle

numeric | Degree to rotate the X labels. One of: 0, 45, 90.

enforce_symmetry

logical | Return a symmetrical plot axes-wise or continuous color scale-wise, when applicable.

min.cutoff, max.cutoff

numeric | Set the min/max ends of the color scale. Any cell/group with a value lower than min.cutoff will turn into min.cutoff and any cell with a value higher than max.cutoff will turn into max.cutoff. In FeaturePlots, provide as many values as features. Use NAs to skip a feature.

diverging.palette

character | Type of symmetrical color palette to use. Out of the diverging palettes defined in brewer.pal.

diverging.direction

numeric | Either 1 or -1. Direction of the divering palette. This basically flips the two ends.

sequential.palette

character | Type of sequential color palette to use. Out of the sequential palettes defined in brewer.pal.

sequential.direction

numeric | Direction of the sequential color scale. Either 1 or -1.

number.breaks

numeric | Controls the number of breaks in continuous color scales of ggplot2-based plots.

use_viridis

logical | Whether to use viridis color scales.

viridis.palette

character | A capital letter from A to H or the scale name as in scale_fill_viridis.

viridis.direction

numeric | Either 1 or -1. Controls how the gradient of viridis scale is formed.

flip

logical | Whether to invert the axis of the displayed plot.

grid.color

character | Color of the grid in the plot. In heatmaps, color of the border of the cells.

border.color

character | Color for the border of the heatmap body.

plot.title.face, plot.subtitle.face, plot.caption.face, axis.title.face, axis.text.face, legend.title.face, legend.text.face

character | Controls the style of the font for the corresponding theme element. One of:

  • plain: For normal text.

  • italic: For text in itallic.

  • bold: For text in bold.

  • bold.italic: For text both in itallic and bold.

Value

A ggplot2 object.

Examples


  # Check Suggests.
  value <- SCpubr:::check_suggests(function_name = "do_ExpressionHeatmap", passive = TRUE)

  if (isTRUE(value)){
    # Consult the full documentation in https://enblacar.github.io/SCpubr-book/

    # Define your Seurat object.
    sample <- readRDS(system.file("extdata/seurat_dataset_example.rds", package = "SCpubr"))

    # Define list of genes.
    genes <- rownames(sample)[1:10]

    # Default parameters.
    p <- SCpubr::do_ExpressionHeatmap(sample = sample,
                                      features = genes,
                                      viridis.direction = -1)
    
    p
  } else if (base::isFALSE(value)){
    message("This function can not be used without its suggested packages.")
    message("Check out which ones are needed using `SCpubr::state_dependencies()`.")
  }


SCpubr documentation built on Oct. 11, 2023, 5:15 p.m.