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Seurat (version 3.1.1)

MixingMetric: Calculates a mixing metric

Description

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.

Usage

MixingMetric(object, grouping.var, reduction = "pca", dims = 1:2,
  k = 5, max.k = 300, eps = 0, verbose = TRUE)

Arguments

object

Seurat object

grouping.var

Grouping variable for dataset

reduction

Which dimensionally reduced space to use

dims

Dimensions to use

k

Neighbor number to examine per group

max.k

Maximum size of local neighborhood to compute

eps

Error bound on the neighbor finding algorithm (from RANN)

verbose

Displays progress bar

Value

Returns a vector of values representing the entropy metric from each bootstrapped iteration.