lunSimulate: Lun simulation

Description Usage Arguments Details Value References Examples

View source: R/lun-simulate.R

Description

Simulate single-cell RNA-seq count data using the method described in Lun, Bach and Marioni "Pooling across cells to normalize single-cell RNA sequencing data with many zero counts".

Usage

1
lunSimulate(params = newLunParams(), verbose = TRUE, ...)

Arguments

params

LunParams object containing Lun simulation parameters.

verbose

logical. Whether to print progress messages.

...

any additional parameter settings to override what is provided in params.

Details

The Lun simulation generates gene mean expression levels from a gamma distribution with shape = mean.shape and rate = mean.rate. Counts are then simulated from a negative binomial distribution with mu = means and size = 1 / bcv.common. In addition each cell is given a size factor (2 ^ rnorm(nCells, mean = 0, sd = 0.5)) and differential expression can be simulated with fixed fold changes.

See LunParams for details of the parameters.

Value

SingleCellExperiment object containing the simulated counts and intermediate values.

References

Lun ATL, Bach K, Marioni JC. Pooling across cells to normalize single-cell RNA sequencing data with many zero counts. Genome Biology (2016).

Paper: dx.doi.org/10.1186/s13059-016-0947-7

Code: https://github.com/MarioniLab/Deconvolution2016

Examples

1
sim <- lunSimulate()

splatter documentation built on Dec. 7, 2018, 6 p.m.