Description Usage Arguments Details Value Examples
Estimate simulation parameters for the ZINB-WaVE simulation from a real dataset.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | 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.
1 2 3 4 5 6 7 8 9 | ## Not run:
# Load example data
library(scater)
data("sc_example_counts")
params <- zinbEstimate(sc_example_counts)
params
## End(Not run)
|
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