splatPopSimulateSC: splatPopSimulateSC

In splatter: Simple Simulation of Single-cell RNA Sequencing Data

Description

Simulate count data for a population from a fictional single-cell RNA-seq experiment using the Splat method.

Usage

splatPopSimulateSC(
  sim.means,
  params,
  key,
  method = c("single", "groups", "paths"),
  counts.only = FALSE,
  sparsify = TRUE,
  verbose = TRUE,
  ...
)

Arguments

sim.means	Matrix or list of matrices of gene means for the population. Output from 'splatPopSimulateMeans()'.
params	SplatPopParams object containing parameters for population scale simulations. See SplatPopParams for details.
key	data.frame object containing a full or partial splatPop key. Output from 'splatPopSimulateMeans()'.
method	which simulation method to use. Options are "single" which produces a single cell population for each sample, "groups" which produces distinct groups (eg. cell types) for each sample (note, this creates separate groups from those created in 'popSimulate' with only DE effects), and "paths" which selects cells from continuous trajectories (eg. differentiation processes).
counts.only	logical. Whether to return only the counts.
sparsify	logical. Whether to automatically convert assays to sparse matrices if there will be a size reduction.
verbose	logical. Whether to print progress messages.
...	any additional parameter settings to override what is provided in params.

Value

SingleCellExperiment object containing simulated counts, intermediate values like the gene means simulated in 'splatPopSimulateMeans', and information about the differential expression and eQTL effects assigned to each gene.

Examples

if (requireNamespace("VariantAnnotation", quietly = TRUE) &&
    requireNamespace("preprocessCore", quietly = TRUE)) {
    params <- newSplatPopParams()
    sim.means <- splatPopSimulateMeans()
    sim <- splatPopSimulateSC(sim.means$means, params, sim.means$key)
}

splatter documentation built on Dec. 3, 2020, 2:01 a.m.