compute.spatial.kld.df: This function is to calculate how likely the cells relevant...

In gsdensity: Density-Based Gene Set Specificity Evaluation

This function is to calculate how likely the cells relevant to multiple gene sets are randomly distributed spatially

Description

This function is to calculate how likely the cells relevant to multiple gene sets are randomly distributed spatially

Usage

## S3 method for class 'spatial.kld.df'
compute(spatial.coords, weight_df, n = 10, n.times = 20)

Arguments

spatial.coords	a data frame with each row as a cell and each column as a spatial coordinate (usually 2: x and y)
weight_df	output of run.rwr.list
n	split the spatial map for local density estimation; n is the number of split for each dimension; for n = 10, the spatial map is split to n * n = 100 grids for the density estimation
n.times	the same as n.times in function 'compute.spatial.kld'

Value

spatial kl-divergence for multiple gene sets

Examples

compute.spatial.kld.df(spatial.coords = coords.df, weight_df = weight_df)

gsdensity documentation built on March 31, 2023, 8:32 p.m.