splatPop simulation

Simulate scRNA-seq count data using the splat model for a population of individuals with correlation structure.

Usage

splatPopSimulate(
  params = newSplatPopParams(nGenes = 50),
  vcf = mockVCF(),
  method = c("single", "groups", "paths"),
  gff = NULL,
  eqtl = NULL,
  means = NULL,
  key = NULL,
  counts.only = FALSE,
  sparsify = TRUE,
  verbose = TRUE,
  ...
)

Arguments

params

SplatPopParams object containing parameters for population scale simulations. See SplatPopParams for details.

vcf

VariantAnnotation object containing genotypes of samples.

method

which simulation method to use. Options are "single" which produces a single population, "groups" which produces distinct groups (eg. cell types), "paths" which selects cells from continuous trajectories (eg. differentiation processes).

gff

Either NULL or a data.frame object containing a GFF/GTF file.

eqtl

Either NULL or if simulating population parameters directly from empirical data, a data.frame with empirical/desired eQTL results. To see required format, run `mockEmpiricalSet()` and see eqtl output.

means

Either NULL or if simulating population parameters directly from empirical data, a Matrix of real gene means across a population, where each row is a gene and each column is an individual in the population. To see required format, run `mockEmpiricalSet()` and see means output.

key

Either NULL or a data.frame object containing a full or partial splatPop key.

counts.only

logical. Whether to save only counts in sce object.

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.

Details

This functions is for simulating data in a single step. It consists of a call to splatPopSimulateMeans, which simulates a mean expression level per gene per sample, followed by a call to splatPopSimulateSC, which uses the splat model to simulate single-cell counts per individual. Please see the documentation for those functions for more details.

See also

splatPopSimulateMeans, splatPopSimulateSC

Examples

# \donttest{
if (requireNamespace("VariantAnnotation", quietly = TRUE) &&
    requireNamespace("preprocessCore", quietly = TRUE)) {
    vcf <- mockVCF()
    gff <- mockGFF()
    sim <- splatPopSimulate(vcf = vcf, gff = gff, sparsify = FALSE)
}
#> Designing population...
#> Simulating data for genes in GFF...
#> Simulating gene means for population...
#> Simulating sc counts for Group1...
#> Done!
# }