muscat_estimation: Estimate Parameters From Real Datasets by muscat

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

Estimate Parameters From Real Datasets by muscat

Description

This function is used to estimate useful parameters from a real dataset by using prepSim function in muscat package.

Usage

muscat_estimation(ref_data, verbose = FALSE, other_prior = NULL, seed)

Arguments

ref_data	A count matrix. Each row represents a gene and each column represents a cell.
verbose	Logical.
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 and other variables are usually customed, so before simulating a dataset you must point it out.
seed	An integer of a random seed.

Details

In muscat, cell group information is not neccessary but users can input it when it is available by other_prior = list(group.condition = xxx).

For more information, see Examples and muscat::prepSim()

Value

A list contains the estimated parameters and the results of execution detection.

References

Crowell H L, Soneson C, Germain P L, et al. Muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data. Nature communications, 2020, 11(1): 1-12. https://doi.org/10.1038/s41467-020-19894-4

Github URL: https://github.com/HelenaLC/muscat

Examples

## Not run: 
ref_data <- simmethods::data
## estimation
estimate_result <- simmethods::muscat_estimation(
  ref_data = ref_data,
  other_prior = NULL,
  verbose = TRUE,
  seed = 111
)

## cell groups
group_condition <- as.numeric(simmethods::group_condition)
## estimation
estimate_result <- simmethods::muscat_estimation(
  ref_data = ref_data,
  other_prior = list(group.condition = group_condition),
  verbose = TRUE,
  seed = 111
)

## End(Not run)

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