kmeans_haystack_highD: Function for k-means clustering of genes according to their...

In singleCellHaystack: A Universal Differential Expression Prediction Tool for Single-Cell and Spatial Genomics Data

Function for k-means clustering of genes according to their distribution in a higher-dimensional space.

Description

Function for k-means clustering of genes according to their distribution in a higher-dimensional space.

Usage

kmeans_haystack_highD(
  x,
  detection,
  genes,
  grid.coordinates = NULL,
  k,
  scale = TRUE,
  ...
)

Arguments

x	Coordinates of cells in a 2D or higher-dimensional space. Rows represent cells, columns the dimensions of the space.
detection	A logical matrix showing which genes (rows) are detected in which cells (columns)
genes	A set of genes (of the 'detection' data) which will be clustered.
grid.coordinates	Coordinates of grid points in the same space as 'x', to be used to estimate densities for clustering.
k	The number of clusters to return.
scale	whether to scale data.
...	Additional parameters which will be passed on to the kmeans function.

Value

An object of class kmeans, describing a clustering into 'k' clusters

Examples

# to be added

singleCellHaystack documentation built on Dec. 28, 2022, 1:29 a.m.