Here we compute a measure of how well mixed a composite dataset is. To compute, we first examine the local neighborhood for each cell (looking at max.k neighbors) and determine for each group (could be the dataset after integration) the k nearest neighbor and what rank that neighbor was in the overall neighborhood. We then take the median across all groups as the mixing metric per cell.
MixingMetric(
object,
grouping.var,
reduction = "pca",
dims = 1:2,
k = 5,
max.k = 300,
eps = 0,
verbose = TRUE
)Seurat object
Grouping variable for dataset
Which dimensionally reduced space to use
Dimensions to use
Neighbor number to examine per group
Maximum size of local neighborhood to compute
Error bound on the neighbor finding algorithm (from RANN)
Displays progress bar
Returns a vector of values representing the entropy metric from each bootstrapped iteration.