Computes the Adjusted Rand Index (ARI) to measure the similarity between
two clustering assignments. The ARI is a measure of agreement between two
partitions, adjusted for chance. Values range from 0 (random partitioning)
to 1 (perfect agreement), with negative values indicating worse than random.
Usage
adjusted_rand_index(seurat_obj, meta1, meta2)
Arguments
- seurat_obj
A Seurat object containing the metadata with clustering assignments
- meta1
Character string specifying the first metadata column name containing
cluster assignments
- meta2
Character string specifying the second metadata column name containing
cluster assignments to compare against meta1
Value
Numeric value representing the Adjusted Rand Index between the two
clustering assignments
Details
The Adjusted Rand Index is calculated using the formula:
ARI = (RI - Expected_RI) / (max(RI) - Expected_RI)
Where:
- RI is the Rand Index
- Expected_RI is the expected value of RI under random partitioning
- max(RI) is the maximum possible value of RI
Examples
if (FALSE) { # \dontrun{
# Compare two clustering results in a Seurat object
ari_score <- adjusted_rand_index(seurat_obj, "seurat_clusters", "leiden_clusters")
} # }