Simulate counts from a pseudotime trajectory using the PhenoPath method.
Usage
phenoSimulate(params = newPhenoParams(), sparsify = TRUE, verbose = TRUE, ...)Arguments
- params
PhenoParams 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
simulate_phenopath that takes a
PhenoParams, 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 simulate_phenopath and the PhenoPath paper for
more details about how the simulation works.
References
Campbell K, Yau C. Uncovering genomic trajectories with heterogeneous genetic and environmental backgrounds across single-cells and populations. bioRxiv (2017).
Paper: 10.1101/159913
Examples
if (requireNamespace("phenopath", quietly = TRUE)) {
sim <- phenoSimulate()
}
#> Simulating counts...
#> Warning: `as_data_frame()` was deprecated in tibble 2.0.0.
#> ℹ Please use `as_tibble()` (with slightly different semantics) to convert to a
#> tibble, or `as.data.frame()` to convert to a data frame.
#> ℹ The deprecated feature was likely used in the phenopath package.
#> Please report the issue to the authors.
#> Warning: The `x` argument of `as_tibble.matrix()` must have unique column names if
#> `.name_repair` is omitted as of tibble 2.0.0.
#> ℹ Using compatibility `.name_repair`.
#> ℹ The deprecated feature was likely used in the tibble package.
#> Please report the issue at <https://github.com/tidyverse/tibble/issues>.
#> Creating final dataset...
#> Sparsifying assays...
#> Automatically converting to sparse matrices, threshold = 0.95
#> Converting 'counts' to sparse matrix: estimated sparse size 0.55 * dense matrix
#> Skipping 'LogExprs': estimated sparse size 1.5 * dense matrix