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Plot Sample Space Visualization

Source: R/plot_sample_space.R
plot_sample_space.Rd

Create a dimensional reduction plot to visualize sample relationships in gene expression space using PCA or UMAP.

Usage

plot_sample_space(
  phyex_set,
  method = c("PCA", "UMAP"),
  colour_by = c("identity", "TXI"),
  seed = 42,
  ...
)

Arguments

phyex_set

A PhyloExpressionSet object (BulkPhyloExpressionSet or ScPhyloExpressionSet)

method

Character string specifying the dimensionality reduction method: "PCA" or "UMAP" (default: "PCA")

colour_by

Character string specifying what to colour by: "identity" (default), "TXI"

seed

Integer seed for reproducible UMAP results (default: 42)

...

Additional arguments passed to specific methods

Value

A ggplot2 object showing the sample space visualisation

Details

This function performs log1p transformation on expression data, removes genes with zero variance, and applies the specified dimensionality reduction method. Samples are coloured by their group assignments or TAI values.

Examples

# Create PCA plot coloured by identity
pca_plot <- plot_sample_space(example_phyex_set, method = "PCA", colour_by = "identity")

# Create UMAP plot coloured by TXI
if (requireNamespace("uwot", quietly = TRUE)) {
    umap_plot <- plot_sample_space(example_phyex_set, method = "UMAP", colour_by = "TXI")
}