scDD_simulation: Simulate Datasets by scDD

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

Simulate Datasets by scDD

Description

This function is used to simulate datasets from learned parameters by scDDSimulate function in Splatter package.

Usage

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

Arguments

parameters	A object generated by splatter::scDDEstimate()
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. Alternatives 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 scDD, users can only set nCells to specify the number of cells because the genes are already fixed after estimation step. See Examples.

References

Korthauer K D, Chu L F, Newton M A, et al. A statistical approach for identifying differential distributions in single-cell RNA-seq experiments. Genome biology, 2016, 17(1): 1-15. https://doi.org/10.1186/s13059-016-1077-y

Bioconductor URL: https://www.bioconductor.org/packages/release/bioc/html/scDD.html

Github URL: https://github.com/kdkorthauer/scDD

Examples

## Not run: 
ref_data <- SingleCellExperiment::counts(scater::mockSCE())
## group information
set.seed(111)
group_condition <- sample(c(1, 2), 200, replace = TRUE)
other_prior <- list(group.condition = group_condition)
## estimation
estimate_result <- simmethods::scDD_estimation(ref_data = ref_data,
                                               other_prior = other_prior,
                                               verbose = TRUE,
                                               seed = 111)

## Simulate 1000 cells
simulate_result <- simmethods::scDD_simulation(parameters = estimate_result[["estimate_result"]],
                                               other_prior = list(nCells = 1000),
                                               return_format = "list",
                                               verbose = TRUE,
                                               seed = 111)
## counts
counts <- simulate_result[["simulate_result"]][["count_data"]]
dim(counts)
## cell information
col_data <- simulate_result[["simulate_result"]][["col_meta"]]
table(col_data$group)
## gene information
row_data <- simulate_result[["simulate_result"]][["row_meta"]]
head(row_data)

## End(Not run)

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