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")
)A SingleCellExperiment object containing numeric expression matrix for the query cells.
A SingleCellExperiment object containing numeric expression matrix for the reference cells.
The column name in the colData of query_data that identifies the cell types.
The column name in the colData of reference_data that identifies the cell types.
A character vector specifying the cell types to include in the plot. If NULL, all cell types are included.
A numeric vector specifying which principal components to include in the plot. Default is 1:5.
Name of the assay on which to perform computations. Default is "logcounts".
Type of plot to use for the lower panels. Either "scatter" (default), "contour", "ellipse", or "blank".
Type of plot to use for the diagonal panels. Either "ridge" (default), "density", or "boxplot".
Type of plot to use for the upper panels. Either "blank" (default), "scatter", "contour", or "ellipse".
A ggmatrix object representing a pairs plot of specified principal components for the given cell types and datasets.
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.