Plot Principal Components for Different Cell Types

This function plots the principal components for different cell types in the query and reference datasets.

plotCellTypePCA(
  query_data,
  reference_data,
  query_cell_type_col,
  ref_cell_type_col,
  cell_types = NULL,
  pc_subset = 1:5,
  assay_name = "logcounts",
  lower_facet = c("scatter", "contour", "ellipse", "blank"),
  diagonal_facet = c("ridge", "density", "boxplot"),
  upper_facet = c("blank", "scatter", "contour", "ellipse"),
  max_cells_query = 2000,
  max_cells_ref = 2000
)

Arguments

query_data

A SingleCellExperiment object containing numeric expression matrix for the query cells.

reference_data

A SingleCellExperiment object containing numeric expression matrix for the reference cells.

query_cell_type_col

The column name in the colData of query_data that identifies the cell types.

ref_cell_type_col

The column name in the colData of reference_data that identifies the cell types.

cell_types

A character vector specifying the cell types to include in the plot. If NULL, all cell types are included.

pc_subset

A numeric vector specifying which principal components to include in the plot. Default is 1:5.

assay_name

Name of the assay on which to perform computations. Default is "logcounts".

lower_facet

Type of plot to use for the lower panels. Either "scatter" (default), "contour", "ellipse", or "blank".

diagonal_facet

Type of plot to use for the diagonal panels. Either "ridge" (default), "density", or "boxplot".

upper_facet

Type of plot to use for the upper panels. Either "blank" (default), "scatter", "contour", or "ellipse".

max_cells_query

Maximum number of query cells to retain after cell type filtering. If NULL, no downsampling of query cells is performed. Default is 2000.

max_cells_ref

Maximum number of reference cells to retain after cell type filtering. If NULL, no downsampling of reference cells is performed. Default is 2000.

Value

A ggmatrix object representing a pairs plot of specified principal components for the given cell types and datasets.

Details

This function projects the query dataset onto the principal component space of the reference dataset and then plots the specified principal components for the specified cell types. It uses the `projectPCA` function to perform the projection and GGally to create the pairs plot.