R/plotGeneSetScores.R
plotGeneSetScores.Rd
Plot gene sets or pathway scores on PCA, TSNE, or UMAP. Single cells are color-coded by scores of gene sets or pathways.
plotGeneSetScores(
se_object,
method = c("PCA", "TSNE", "UMAP"),
score_col,
pc_subset = 1:5,
cell_type_col = NULL,
cell_types = NULL,
max_cells = 2500
)
An object of class SingleCellExperiment
containing numeric expression matrix and other metadata.
It can be either a reference or query dataset.
A character string indicating the method for visualization ("PCA", "TSNE", or "UMAP").
A character string representing the name of the score_col (score) in the colData(se_object) to plot.
An optional vector specifying the principal components (PCs) to include in the plot if method = "PCA". Default is 1:5.
The column name in the colData
of se_object
that identifies the cell types.
A character vector specifying the cell types to include in the plot. If NULL, all cell types are included.
Maximum number of cells to retain. If the object has fewer cells, it is returned unchanged. Default is 2500.
A ggplot2 object representing the gene set scores plotted on the specified reduced dimensions.
This function plots gene set scores on reduced dimensions such as PCA, t-SNE, or UMAP.
It extracts the reduced dimensions from the provided SingleCellExperiment
object.
Gene set scores are visualized as a scatter plot with colors indicating the scores.
For PCA, the function automatically includes the percentage of variance explained
in the plot's legend.
# Load data
data("query_data")
# Plot gene set scores on PCA
plotGeneSetScores(se_object = query_data,
method = "PCA",
score_col = "gene_set_scores",
pc_subset = 1:5,
cell_types = "CD8",
cell_type_col = "SingleR_annotation")