simulateDataset: Simulate an unrealistic spatial omics dataset.

In prabhakarlab/Banksy: Spatial transcriptomic clustering

Simulate an unrealistic spatial omics dataset.

Description

Simulate an unrealistic spatial omics dataset.

Usage

simulateDataset(n_cells = 300, n_genes = 30, n_rings = 3, rate = 10)

Arguments

n_cells	An integer scalar specifying the approximate number of cells.
n_genes	An integer scalar specifying the number of genes.
n_rings	An integer scalar specifying the number of spatial rings.
rate	A numeric scalar specifying the Poisson rate parameter for simulating counts.

Details

This function generates an unrealistic spatial omics dataset based on a user-specified number of cells and genes. The number of clusters is defined by n_rings, while counts follow a Poisson distribution with a user-specified rate rate. The simulation is set up such that the number of cells in each cluster is uniformly distributed; as such, the final number of cells is approximately equal to the user-specified number of cells.

Value

A SpatialExperiment object.

Examples

set.seed(2023)
rings <- simulateDataset(n_cells = 5e3, n_genes = 50, n_rings = 8)
rings
table(rings$cluster)
df <- cbind.data.frame(
    SummarizedExperiment::colData(rings), 
    SpatialExperiment::spatialCoords(rings))
library(ggplot2)
ggplot(df, aes(x=x, y=y, col=cluster)) + geom_point() + theme_classic()

prabhakarlab/Banksy documentation built on April 11, 2024, 2:45 p.m.