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".
LunParams object containing Lun simulation parameters.
logical. Whether to print progress messages.
any additional parameter settings to override what is provided in
The Lun simulation generates gene mean expression levels from a gamma
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.
LunParams for details of the parameters.
SingleCellExperiment object containing the simulated counts and intermediate values.
Lun ATL, Bach K, Marioni JC. Pooling across cells to normalize single-cell RNA sequencing data with many zero counts. Genome Biology (2016).
sim <- lunSimulate()
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