Plot summarized eigengenes as a heatmap

Plots the mean eigengene (or the mean of other types of summarized module expression profile) per cell type and species as a heatmap.

Usage

plotSumEigengeneHeatmap(
  eigengenes,
  expr_column = "eigengene",
  cell_type_column = "cell_type",
  heatmap_colors = NULL,
  species_colors = NULL,
  cell_type_colors = NULL,
  clip = 3,
  font_size = 14,
  label_size = font_size/3
)

Arguments

eigengenes

Data frame of eigengenes, required columns:

cell: Character, the cell barcode.
species: Character, the name of the species.
{{cell_type_column}}: Character, cell type annotation.
module: Character, transcriptional regulator and in case the eigengene was calculated for the positively or negatively regulated targets only, the direction of regulation (format: nameOfRegulator(+) or nameOfRegulator(-)).
{{expr_column}}: Numeric, summarized module expression profiles (typically the eigengene, the mean expression of the module, or the expression of the regulator).

expr_column

Character specifying the column of eigengenes by which the heatmap should be colored. This column is expected to contain summarized module expression profiles, typically the eigengene (default: "eigengene"), the mean expression of the module, or the expression of the regulator.

cell_type_column

Character, the name of the cell type annotation column in eigengenes (default: "cell_type").

heatmap_colors

Character vector, the heatmap colors for the summarized expression levels. The vector can contain any number of colors that will be passed on to and converted into a continuous scale by scale_color_gradientn.

species_colors

Character vector, colors per species.

cell_type_colors

Character vector, colors per cell type.

clip

Numeric specifying the degree of clipping. For each gene, the expression level values that are more standard deviations away from the mean than clip are treated as NA. The default is 3 meaning that expression levels are clipped to the range of mean \(\pm\) 3\(\sigma\) per gene.

font_size

Numeric, font size (default: 14).

label_size

Numeric, font size of the cell type labels (default: font_size / 5).

Value

A heatmap as a ggplot object showing the summarized expression levels of the modules per cell type and species.

Details

A concept adapted from WGCNA, the eigengene summarizes the expression profile of an entire module, and it is calculated as the first principal component of the module expression data (see also calculateEigengenes). Other possible ways of representing the expression profile of a module include the mean expression and the regulator expression.

The function takes a data frame containing any of these summarized module expression profiles as input (normally the output of calculateEigengenes) and plots it as a heatmap, with columns corresponding to cell types, rows corresponding to modules and species, and colors corresponding to the mean module expression across all cells of the given cell type and species.

The column of the data frame containing the chosen type of summarized expression profile can be specified by the parameter expr_column (default: "eigengene"). The colors to represent the expression levels can be controlled by the parameter heatmap_colors.

If the eigengene (or mean expression) has been calculated for positively and negatively regulated targets separately, then these will appear as separate rows of the heatmap.

The cell types and species are visualized as annotation graphics above the heatmap using cell_type_colors and on the right hand side of the heatmap using species_colors, respectively.

Expression levels are clipped to the range of mean \(\pm\) 3\(\sigma\) per module, this can be changed via the parameter clip. Clipping aids visualization by preventing the outlier data points from squishing the rest of the data into a small color range. If clipping is not desired, please set clip to Inf.

References

Zhang, B., & Horvath, S. (2005). A general framework for weighted gene co-expression network analysis. Statistical Applications in Genetics and Molecular Biology, 4, 17-60. https://doi.org/10.2202/1544-6115.1128

Examples

plotSumEigengeneHeatmap(eigengenes)