PROSSTT_simulation: Simulate Datasets by PROSSTT

In duohongrui/simmethods: A collection of 40+ simulation methods for singlce-cell RNA seqencing data

Simulate Datasets by PROSSTT

Description

Simulate Datasets by PROSSTT

Usage

PROSSTT_simulation(
  parameters,
  other_prior = NULL,
  return_format,
  verbose = FALSE,
  seed
)

Arguments

parameters	A object generated by simutils::make_trees()
other_prior	A list with names of certain parameters. Some methods need extra parameters to execute the estimation step, so you must input them. In simulation step, the number of cells, genes, groups, batches, the percent of DEGs are usually customed, so before simulating a dataset you must point it out. See Details below for more information.
return_format	A character. Alternative choices: list, SingleCellExperiment, Seurat, h5ad. If you select h5ad, you will get a path where the .h5ad file saves to.
verbose	Logical. Whether to return messages or not.
seed	A random seed.

Details

In PROSSTT, nCells and nGenes are usually customed and users can set other_prior = list(nCells = 1000, nGenes = 2000) to simulate 1000 cells and 5000 genes. For more parameters and documents, see Examples and simmethods::get_method("PROSSTT").

References

Papadopoulos N, Gonzalo P R, Söding J. PROSSTT: probabilistic simulation of single-cell RNA-seq data for complex differentiation processes. Bioinformatics, 2019, 35(18): 3517-3519. https://doi.org/10.1093/bioinformatics/btz078

Github URL: https://github.com/soedinglab/prosstt/

Document URL: http://wwwuser.gwdg.de/~compbiol/prosstt/doc/

Examples

ref_data <- simmethods::data
## estimation
estimate_result <- simmethods::PROSSTT_estimation(
  ref_data = ref_data,
  other_prior = NULL,
  verbose = TRUE,
  seed = 111
)

# 1) Simulate with default parameters
simulate_result <- simmethods::PROSSTT_simulation(
  parameters = estimate_result[["estimate_result"]],
  other_prior = NULL,
  return_format = "list",
  verbose = TRUE,
  seed = 111
)
## counts
counts <- simulate_result[["simulate_result"]][["count_data"]]
dim(counts)

# 2) 2000 cells and 5000 genes
simulate_result <- simmethods::PROSSTT_simulation(
  parameters = estimate_result[["estimate_result"]],
  other_prior = list(nCells = 2000,
                     nGenes = 5000),
  return_format = "list",
  verbose = TRUE,
  seed = 111
)

## counts
counts <- simulate_result[["simulate_result"]][["count_data"]]
dim(counts)

duohongrui/simmethods documentation built on June 17, 2024, 10:49 a.m.