scDesign2_estimation | R Documentation |
This function is used to estimate useful parameters from a real dataset by
using fit_model_scDesign2
function in scDesign2 package.
scDesign2_estimation(ref_data, verbose = FALSE, other_prior = NULL, seed)
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 are usually customed, so before simulating a dataset you must point it out.
See |
seed |
An integer of a random seed. |
In scDesign2, users can input cell group or cell type information before estimating
parameters from real datasets. For more instructions or information, see Examples
or scDesign2::fit_model_scDesign2()
A list contains the estimated parameters and the results of execution detection.
Sun T, Song D, Li W V, et al. scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured. Genome biology, 2021, 22(1): 1-37. https://doi.org/10.1186/s13059-021-02367-2
Github URL: https://github.com/JSB-UCLA/scDesign2
## Not run:
ref_data <- simmethods::data
## cell groups
group_condition <- as.numeric(simmethods::group_condition)
## In scDesign2, cell group information is not neccessary which indicates the type
## that each cell belongs to.
estimate_result <- simmethods::scDesign2_estimation(
ref_data = ref_data,
other_prior = list(group.condition = group_condition),
verbose = TRUE,
seed = 111
)
## Or you can input information of cell types via cell_type_sel parameter described
## in scDesign2::fit_model_scDesign2 function
estimate_result <- simmethods::scDesign2_estimation(
ref_data = ref_data,
other_prior = list(cell_type_sel = paste0("cell_type",
group_condition)),
verbose = TRUE,
seed = 111
)
## End(Not run)
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