spearmandist

Computes pairwise Spearman distances between group centroids (mean embedding vectors) in a Seurat object.

Usage

.spearmandist(seurat_object, groupby, reduction, verbose = TRUE)

Arguments

seurat_object

A Seurat object.

groupby

A character scalar giving the name of a metadata column in seurat_object@meta.data that defines group labels.

reduction

A character scalar giving the name of a dimensional reduction (e.g., "pca", "harmony") used for distance calculations. This should be a geometry-preserving representation; visualization-oriented nonlinear embeddings (e.g., "umap", "tsne") are not recommended for distance computation.

verbose

Logical; if TRUE, prints progress messages.

Value

A symmetric data.frame (groups \(\times\) groups) containing pairwise Spearman distances between group centroids.

Details

Cells are grouped according to groupby. For each group, a centroid is computed as the column-wise mean of cell embeddings in the specified reduction space. Spearman's rank correlation coefficient is then computed between all pairs of group centroids and converted to a distance measure as \(1 - \rho\).

This metric captures monotonic similarity between group-level expression profiles and is insensitive to absolute scale, but does not account for within-group heterogeneity or higher-order distributional differences.