hclust_haystack_highD: Function for hierarchical clustering of genes according to...

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

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

Description

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

Usage

hclust_haystack_highD(
  x,
  detection,
  genes,
  method = "ward.D",
  grid.coordinates = NULL,
  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.
method	The method to use for hierarchical clustering. See '?hclust' for more information. Default: "ward.D".
grid.coordinates	Coordinates of grid points in the same space as 'x', to be used to estimate densities for clustering.
scale	whether to scale data.

Value

An object of class hclust, describing a hierarchical clustering tree.

Examples

# to be added

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