Simulate counts from a simple negative binomial distribution without simulated library sizes, differential expression etc.
Usage
simpleSimulate(
params = newSimpleParams(),
sparsify = TRUE,
verbose = TRUE,
...
)Arguments
- params
SimpleParams 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
Gene means are simulated 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 / counts.disp. See SimpleParams for more
details of the parameters.
Examples
sim <- simpleSimulate()
#> Simulating means...
#> Simulating counts...
#> Creating final dataset...
#> Sparsifying assays...
#> Automatically converting to sparse matrices, threshold = 0.95
#> Converting 'counts' to sparse matrix: estimated sparse size 0.64 * dense matrix
# Override default parameters
sim <- simpleSimulate(nGenes = 1000, nCells = 50)
#> Simulating means...
#> Simulating counts...
#> Creating final dataset...
#> Sparsifying assays...
#> Automatically converting to sparse matrices, threshold = 0.95
#> Converting 'counts' to sparse matrix: estimated sparse size 0.65 * dense matrix