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(phyex_set, method = "PCA", colour_by = "identity")
# Create UMAP plot coloured by TXI
# umap_plot <- plot_sample_space(phyex_set, method = "UMAP", colour_by = "TXI")
