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 )

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 |

Returns a vector of values of the mixing metric for each cell