simulateCells.celda_C: Simulate cells from the celda_C model

In compbiomed/celda: CEllular Latent Dirichlet Allocation

Description

Generates a simulated counts matrix, cell subpopulation clusters, and sample labels according to the generative process of the celda_C model.

Usage

## S3 method for class 'celda_C'
simulateCells(model, S = 5, C.Range = c(50, 100),
  N.Range = c(500, 1000), G = 100, K = 5, alpha = 1, beta = 1,
  seed = 12345, ...)

Arguments

model	Character. Options available in 'celda::available.models'.
S	Integer. Number of samples to simulate. Default 5.
C.Range	Vector of length 2 given the range (min,max) of number of cells for each sample to be randomly generated from the uniform distribution. Default c(50, 100).
N.Range	Integer vector. A vector of length 2 that specifies the lower and upper bounds of the number of counts generated for each cell. Default c(500, 1000).
G	Integer. The total number of features to be simulated. Default 100.
K	Integer. Number of cell populations. Default 5.
alpha	Numeric. Concentration parameter for Theta. Adds a pseudocount to each cell population in each sample. Default 1.
beta	Numeric. Concentration parameter for Phi. Adds a pseudocount to each feature in each cell population. Default 1.
seed	Integer. Passed to 'set.seed()'. Default 12345.
...	Additional parameters.

Value

List. Contains the simulated matrix 'counts', cell population clusters 'z', sample assignments 'sample.label', and input parameters.

See Also

'celda_G()' for simulating feature modules and 'celda_CG()' for simulating feature modules and cell populations.

Examples

celda.c.sim = simulateCells(model="celda_C", K=10)
sim.counts = celda.c.sim$counts

compbiomed/celda documentation built on May 25, 2019, 3:58 a.m.