Estimate simulation parameters for the scDD simulation from a real dataset.
scDDEstimate(counts, params = newSCDDParams(), verbose = TRUE, BPPARAM = SerialParam(), ...) # S3 method for matrix scDDEstimate(counts, params = newSCDDParams(), verbose = TRUE, BPPARAM = SerialParam(), conditions, ...) # S3 method for SingleCellExperiment scDDEstimate(counts, params = newSCDDParams(), verbose = TRUE, BPPARAM = SerialParam(), condition = "condition", ...) # S3 method for default scDDEstimate(counts, params = newSCDDParams(), verbose = TRUE, BPPARAM = SerialParam(), condition, ...)
counts | either a counts matrix or a SingleCellExperiment object containing count data to estimate parameters from. |
---|---|
params | SCDDParams object to store estimated values in. |
verbose | logical. Whether to show progress messages. |
BPPARAM | A |
... | further arguments passed to or from other methods. |
conditions | Vector giving the condition that each cell belongs to. Conditions can be 1 or 2. |
condition | String giving the column that represents biological group of interest. |
SCDDParams object containing the estimated parameters.
This function applies preprocess
to the counts then uses
scDD
to estimate the numbers of each gene type to
simulate. The output is then converted to a SCDDParams object. See
preprocess
and scDD
for details.
# NOT RUN { # Load example data library(scater) data("sc_example_counts") conditions <- sample(1:2, ncol(sc_example_counts), replace = TRUE) params <- scDDEstimate(sc_example_counts, conditions) params # }