Heatmap of gene expression in each cell — Cell

This function generates a heatmap to visualize the expression of features in each cell of a Seurat object. Credits to Ming Tang for the initial idea to replicate DoHeatmap using ComplexHeatmap. Various new parameters were added to offer more flexibility and customization.

Usage

Cell_Heatmap(
  seurat_object,
  assay = "RNA",
  layer = "data",
  features,
  split.by = NULL,
  idents = NULL,
  split.idents = NULL,
  scale = TRUE,
  rescale = FALSE,
  rescale.range = c(0, 3),
  rotate.axis = FALSE,
  col.min = ifelse(isTRUE(scale), -2, 0),
  col.max = ifelse(isTRUE(scale), 2, "q100"),
  data.colors = if (isTRUE(scale)) c("#35A5FF", "white", "red") else "Viridis",
  palette.reverse = FALSE,
  na.color = "grey40",
  idents.colors = NULL,
  show.idents.names.colors = TRUE,
  show.idents.oppo.colors = FALSE,
  split.colors = NULL,
  show.split.names.colors = TRUE,
  show.split.oppo.colors = FALSE,
  order.idents = NULL,
  order.split = NULL,
  order.colors = TRUE,
  kmeans.repeats = 100,
  shuffle.cells = TRUE,
  cluster.cells = FALSE,
  cluster.features = TRUE,
  features.kmeans = 1,
  features.kmeans.numbers.size = 11,
  idents.gap = 1,
  features.gap = 1,
  idents.names.size = 9,
  features.names.size = 9,
  features.names.style = "italic",
  row.names.side = "left",
  row.names.width = 15,
  column.names.angle = 45,
  column.names.side = "top",
  column.names.height = 15,
  outer.border = TRUE,
  data.legend.name = ifelse(isTRUE(scale), "Z-Score", "Expression"),
  data.legend.side = "bottom",
  data.legend.direction = "horizontal",
  data.legend.position = "topcenter",
  data.legend.width = 5,
  idents.legend.name = "Clusters",
  show.idents.legend = TRUE,
  split.legend.name = split.by,
  show.split.legend = TRUE,
  legend.title.size = 10,
  legend.text.size = 10,
  legend.gap = 10,
  raster = ifelse(ncol(seurat_object) > 3000, TRUE, FALSE),
  raster.quality = 10,
  output.data = FALSE,
  ...
)

Arguments

seurat_object: A Seurat object.
assay: Character. The name of an assay containing the layer with the expression matrix. If the seurat_object contains multiple 'RNA' assays, you may specify which one to use (for example, 'RNA2' if you have created a second 'RNA' assay you named 'RNA2'. See Seurat v5 vignettes for more information). You may also use another assay, such as 'SCT', to pull feature expression from.
layer: Character. The name of a layer (formerly known as slot) which stores the expression matrix. It is recommended to use 'data'.
features: Character. The names of one or several features to plot the cell expression from.
split.by: Character. The name of a metadata (for example, 'orig.ident', 'seurat_clusters', etc) to split the identities of the active.ident metadata by.
idents: Character. The names of one or several identities in the active.ident metadata to select. If NULL, all identities are used.
split.idents: Character. The names of one or several split.by identities to select. If NULL, all identities are used. Ignored if split.by = NULL.
scale: Logical. If TRUE, cell expression values will be scaled using scale and default parameters. The resulting values will be Z-scores (mean subtracted values divided by standard deviation) and not positive cell expression values anymore, which is why there will be positive and negative values displayed, depending on if the expression in a particular cell is below or above the mean expression from all cells (which is calculated independently for each feature).
rescale: Logical. If TRUE, cell expression values will be adjusted using rescale between the first numerical value of rescale.range (lowest expression) and the second numerical value (highest expression). This is different than scale as this doesn't compare values to any mean and standard deviation and is therefore not a Z-score, it only refits each cell expression value (independently for each feature) in order to visualize all features in the same dimension regardless of their differences in levels of expression. Ignored if scale = TRUE.
rescale.range: Numeric. The minimum and maximum values to resize the cell expression values and internally passed to rescale. These values are arbitrary and will not change the visualization, only the values in the legend, you need to adjust col.min and col.max to influence the color scale. Ignored if rescale = FALSE or scale = TRUE.
rotate.axis: Logical. If TRUE, flips the axis, so that features are displayed as columns and identities as rows.
col.min: Character or Numeric. The minimum value for the breaks internally passed to colorRamp2. If character, must be a quantile in the form 'qX' where X is a number between 0 and 100. A value of 'q5' or 'q10' is useful to reduce the effect of outlier values (i.e. a very low value that significantly alters the color scale range of all other values).
col.max: Character or Numeric. The maximum value for the breaks internally passed to colorRamp2. If character, must be a quantile in the form 'qX' where X is a number between 0 and 100. A value of 'q95' or 'q90' is useful to reduce the effect of outlier values (i.e. a very high value that significantly alters the color scale range of all other values).
data.colors: Character or Function. Either three color names, corresponding to the lowest, zero (or middle if scale = FALSE), and highest values in the expression matrix and internally passed to colorRamp2, or two color names, corresponding to the lowest and highest values, or the name of a palette and internally passed to hcl_palette in colorRamp2 (such as 'Inferno', 'Berlin', 'Viridis' etc, check hcl.pals for all palettes available), or a custom colorRamp2 function.
palette.reverse: Logical. If TRUE and if data.colors is a palette (such as 'Viridis'), the function will reverse its colors.
na.color: Character. The color name for missing values (NA).
idents.colors: Character. The color names for each identity of the active.ident metadata or in idents. If NULL, uses Seurat's default colors.
show.idents.names.colors: Logical. If TRUE, the function will display the colors specified in idents.colors next to identity names.
show.idents.oppo.colors: Logical. If TRUE, the function will display the colors specified in idents.colors on the opposite side of identity names.
split.colors: Character. The color names for each split.by identity or in split.idents. If NULL, uses a custom set of colors from colors. Ignored if split.by = NULL.
show.split.names.colors: Logical. If TRUE, the function will display the colors specified in split.colors next to identity names. Ignored if split.by = NULL.
show.split.oppo.colors: Logical. If TRUE, the function will display the colors specified in split.colors on the opposite side of identity names. Ignored if split.by = NULL.
order.idents: Character or Numeric. Either 'reverse', or the identities (as names or as numerical values corresponding to the indices) of the active.ident metadata or in idents to order the cells.
order.split: Character or Numeric. Either 'reverse', or the split.by identities (as names or as numerical values corresponding to the indices) or in split.idents to order the cells. Ignored if split.by = NULL.
order.colors: Logical. If TRUE, the data.colors and split.colors will automatically be ordered according to order.idents and order.split. Ignored if order.idents and order.split are NULL.
kmeans.repeats: Numeric. The number of runs to get a consensus K-means clustering. Ignored if features.kmeans = 1.
shuffle.cells: Logical. If TRUE, the function will randomize the distribution of cells in each identity. Useful to smooth expression, which limits visible batch effect (cells in a merged Seurat object are typically ordered based on the levels of the 'orig.ident' metadata, this might lead to unwanted patterns of expression in another metadata). Note that no values are modified, it only changes the order of cells in each identity. Ignored if cluster.cells = TRUE.
cluster.cells: Logical. If TRUE, the function will cluster the cells within each identity. Will have the opposite effect of shuffle.cells, as it will order cells based on their expression similarity and will therefore increase batch effect. Useful to visualize if, within an identity, a subset of cells have high expression while the rest of the cells have low expression, or vice versa. Just like shuffle.cells, no values are modified, it only changes the order of cells in each identity.
cluster.features: Logical or Function. If TRUE, the function will cluster the features. You may also pass an hclust or dendrogram object which contains clustering.
features.kmeans: Numeric. The number of slices to use for feature K-means clustering.
features.kmeans.numbers.size: Numeric. The font size of the feature K-means slice numbers. Set to 0 to remove them.
idents.gap: Numeric. The gap between the identity slices.
features.gap: Numeric. The gap between the feature slices. Ignored if features.kmeans = 1.
idents.names.size: Numeric. The font size of the identity names. Set to 0 to remove them.
features.names.size: Numeric. The font size of the feature names. Set to 0 to remove them.
features.names.style: Character. The font face of the feature names. The Gene nomenclature used by almost all scientific journals require that feature names are italicized, therefore the parameter is by default set to 'italic'. Use 'plain' to revert back to regular font face.
row.names.side: Character. The side where the row names will be displayed, either 'left' or 'right'. The dendrogram will be displayed on the opposite side.
row.names.width: Numeric. The width of the row names. Increase this parameter if your row names are truncated.
column.names.angle: Numeric. The angle of rotation of the column names.
column.names.side: Character. The side where the column names will be displayed, either 'top' or 'bottom'. The dendrogram will be displayed on the opposite side.
column.names.height: Numeric. The height of the column names. Increase this parameter if your column names are truncated.
outer.border: Logical. If TRUE, the function will display an outer border around the heatmap or around each slice if features.kmeans > 1.
data.legend.name: Character. The name of the data legend.
data.legend.side: Character. The side where the data legend will be displayed, either 'left', 'right', 'top' or 'bottom'.
data.legend.direction: Character. The direction of the data legend, either 'horizontal' or 'vertical'.
data.legend.position: Character. The centering of the data legend name, there are many options, default option from Heatmap is 'topleft'.
data.legend.width: Numeric. How long the data legend will be, only affects the data legend if data.legend.direction = 'horizontal'.
idents.legend.name: Character. The name of the active.ident metadata legend. Ignored if show.idents.names.colors and show.idents.oppo.colors are FALSE.
show.idents.legend: Logical. If TRUE, the function will display a legend for the active.ident metadata identities or idents. Ignored if show.idents.names.colors and show.idents.oppo.colors are FALSE.
split.legend.name: Character. The name of the split.by legend. Ignored if split.by = NULL. Ignored if show.split.names.colors and show.split.oppo.colors are FALSE.
show.split.legend: Logical. If TRUE, the function will display a legend for the split.by identities or split.idents. Ignored if show.split.names.colors and show.split.oppo.colors are FALSE.
legend.title.size: Numeric. The font size of all legend titles.
legend.text.size: Numeric. The font size of all legend texts.
legend.gap: Numeric. The gap between the legends and the heatmap. This parameter sets the value in the global options of ht_opt, so it will affect all Heatmap objects in the same R session. Use ComplexHeatmap::ht_opt(RESET = TRUE) to restore default parameters.
raster: Logical. (from Heatmap documentation) If TRUE, the function will render the heatmap body as a raster image. It helps to reduce file size when the matrix is huge.
raster.quality: Numeric. The quality of the raster image. A higher value will slow rendering but will lower expression smoothing. Ignored if raster = FALSE.
output.data: Logical. If TRUE, the function will return a matrix object of the cell expression data, scaled or not, instead of displaying anything.
...: Additional arguments to be passed to Heatmap, such as show_parent_dend_line, clustering_method_rows, etc, accepts any parameter that wasn't already internally passed to Heatmap (for example, outer.border sets the border parameter of Heatmap, so you will get an error if you try to pass the border parameter in Cell_Heatmap).

Value

A Heatmap object, or a matrix object of the cell expression data, scaled or not.

Examples

# Prepare data
pbmc3k <- Right_Data("pbmc3k")
pbmc3k.markers = c("CCR7", "TCF7", "S100A9", "CD14",
                 "CD40LG", "CD2", "CD79A", "TCL1A",
                 "CCL5", "CD8A", "CDKN1C", "MS4A4A",
                 "GNLY", "GZMB")

# Example 1: default parameters
Cell_Heatmap(pbmc3k,
             features = pbmc3k.markers)