sparseDCSimulate: SparseDC simulation

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

Description

Simulate counts from cluster in two conditions using the SparseDC method.

Usage

sparseDCSimulate(
  params = newSparseDCParams(),
  sparsify = TRUE,
  verbose = TRUE,
  ...
)

Arguments

params	SparseDCParams object containing simulation parameters.
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.

Details

This function is just a wrapper around sim_data that takes a SparseDCParams, runs the simulation then converts the output from log-expression to counts and returns a SingleCellExperiment object. The original simulated log-expression values are returned in the LogExprs assay. See sim_data and the SparseDC paper for more details about how the simulation works.

Value

SingleCellExperiment containing simulated counts

References

Campbell K, Yau C. Uncovering genomic trajectories with heterogeneous genetic and environmental backgrounds across single-cells and populations. bioRxiv (2017).

Barron M, Zhang S, Li J. A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data. Nucleic Acids Research (2017).

Paper: 10.1093/nar/gkx1113

Examples

if (requireNamespace("SparseDC", quietly = TRUE)) {
    sim <- sparseDCSimulate()
}

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