sparseDCSimulate {splatter} | R Documentation

## SparseDC simulation

### Description

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

### Usage

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

### Arguments

`params` | SparseDCParams object containing simulation parameters.
`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

    sim <- sparseDCSimulate()

[Package splatter version 1.4.3 Index]