zinbEstimate {splatter} | R Documentation |
Estimate simulation parameters for the ZINB-WaVE simulation from a real dataset.
zinbEstimate( counts, design.samples = NULL, design.genes = NULL, common.disp = TRUE, iter.init = 2, iter.opt = 25, stop.opt = 1e-04, params = newZINBParams(), verbose = TRUE, BPPARAM = SerialParam(), ... ) ## S3 method for class 'SingleCellExperiment' zinbEstimate( counts, design.samples = NULL, design.genes = NULL, common.disp = TRUE, iter.init = 2, iter.opt = 25, stop.opt = 1e-04, params = newZINBParams(), verbose = TRUE, BPPARAM = SerialParam(), ... ) ## S3 method for class 'matrix' zinbEstimate( counts, design.samples = NULL, design.genes = NULL, common.disp = TRUE, iter.init = 2, iter.opt = 25, stop.opt = 1e-04, params = newZINBParams(), verbose = TRUE, BPPARAM = SerialParam(), ... )
counts |
either a counts matrix or a SingleCellExperiment object containing count data to estimate parameters from. |
design.samples |
design matrix of sample-level covariates. |
design.genes |
design matrix of gene-level covariates. |
common.disp |
logical. Whether or not a single dispersion for all features is estimated. |
iter.init |
number of iterations to use for initialization. |
iter.opt |
number of iterations to use for optimization. |
stop.opt |
stopping criterion for optimization. |
params |
ZINBParams object to store estimated values in. |
verbose |
logical. Whether to print progress messages. |
BPPARAM |
A |
... |
additional arguments passes to |
The function is a wrapper around zinbFit
that takes
the fitted model and inserts it into a ZINBParams
object. See
ZINBParams
for more details on the parameters and
zinbFit
for details of the estimation procedure.
ZINBParams object containing the estimated parameters.
if (requireNamespace("zinbwave", quietly = TRUE)) { library(scater) set.seed(1) sce <- mockSCE(ncells = 20, ngenes = 100) params <- zinbEstimate(sce) params }