ComputeDistance

Computes pairwise distances between groups (cell states) in a Seurat object using one of several distance metrics.

Usage

ComputeDistance(
  seurat_object,
  groupby,
  reduction,
  method = c("edist", "euclidean", "spearman"),
  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.

method

A character scalar specifying the distance metric to use. Supported options are "euclidean", "edist" (Energy distance), and "spearman".

verbose

Logical; if TRUE, prints progress messages.

Value

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

Details

Groups are defined by groupby. Distances are computed in a specified low-dimensional representation (reduction) that preserves meaningful transcriptional geometry (e.g., PCA or Harmony). Depending on method, distances are computed between group centroids (Euclidean, Spearman) or between full cell distributions (Energy distance).

Visualization-oriented nonlinear embeddings (e.g., UMAP or t-SNE) are not recommended for distance-based calculations.

Examples

# Euclidean distance between group centroids
ComputeDistance(seurat_object, groupby = "Diagnosis",
                reduction = "pca", method = "euclidean")
#> Error: object 'seurat_object' not found

# Energy distance between group distributions
ComputeDistance(seurat_object, groupby = "Diagnosis",
                reduction = "pca", method = "edist")
#> Error: object 'seurat_object' not found

# Spearman distance between group centroids
ComputeDistance(seurat_object, groupby = "Diagnosis",
                reduction = "pca", method = "spearman")
#> Error: object 'seurat_object' not found