Distances.UMAP: Calculation of cell-cell distances after UMAP

In JSB-UCLA/scDED: Single-cell Dubious Embedding Detector

Calculation of cell-cell distances after UMAP

Description

This function calculates the distances between cells in the post-embedding space for the original and permuted data

Usage

Distances.UMAP(pbmc,pbmc.permuted, K,  n= 30, m = 0.3, pre_embedding = 'pca', rerun = T)

Arguments

pbmc	The original Seurat object
pbmc_permuted	The permuted Seurat object, i.e. the output of Permuted.
K	The number of PCs to use
n	The n.neighbors hyperparameter for UMAP, default = 30
m	The min.dist hyperparameter for UMAP, default = 0.3
pre_embedding	Which embedding use as input for UMAP, default = 'pca'. If the user would like to use an alternate method, like ICA, they should perform that method for the original and permuted data, then specify the slot name here
rerun	This is a time-saving argument (default = T). If the user has already performed dimension reduction and would only like to check the results of that dimension reduction, then they can use rerun=F so scDEED does not re-run the embedding method on the data. In most cases, rerun=T because if you are optimizing hyperparameters, the function will need to rerun the embedding method.

Value

Returns a list with two distance matrices, (1) 'reduced_dim_distances': a matrix showing the distances between cells in the original post-embedding space (2) 'reduced_dim_distances_permuted': a matrix showing the distances between cells in the permuted post-embedding space

JSB-UCLA/scDED documentation built on Feb. 8, 2025, 11:12 a.m.