Seurat Mixing Metric — calc_seurat_mixing

Calculates the mixing metric originally proposed in Seurat (Stuart et al., Cell 2019) and adapted by CellMixS. For each cell, finds the rank of the k_pos-th neighbor from each batch in the sorted neighborhood, and computes the median rank across batches.

Usage

calc_seurat_mixing_metric(coords, batch_info, k = 300, k_pos = 5)

Arguments

coords: Matrix of cell coordinates (cells x dimensions).
batch_info: Factor or character vector of batch assignments.
k: Maximum neighborhood size to search. Default is 300.
k_pos: The rank position to extract per batch. Default is 5.

Value

A named list:

mixing_metrics: Numeric vector of median ranks per cell
mean_mixing_metric: Mean mixing rank (lower indicates better mixing)
median_mixing_metric: Median mixing rank

Examples

coords <- matrix(stats::rnorm(100), 50, 2)
batch <- factor(rep(c("B1", "B2"), length.out = 50))
calc_seurat_mixing_metric(coords, batch)
#> $mixing_metrics
#>  [1] 10.5  8.5  9.5  9.0  9.5 11.5 11.0 10.5  9.5  9.0 10.0  9.5 10.0 10.0  9.0
#> [16] 10.0  9.5  9.0 10.0 11.5 10.5 10.5 10.0 10.0  9.5  9.5  9.0  9.5  9.5  9.0
#> [31]  9.0 10.0  9.5 10.0 11.0  9.0 10.0  9.5  9.5  8.0 10.5 10.5  9.5 10.0  9.0
#> [46] 10.0  9.5 10.0  9.0  9.5
#> 
#> $mean_mixing_metric
#> [1] 9.74
#> 
#> $median_mixing_metric
#> [1] 9.5
#>