Description Usage Arguments Details Value Examples
Estimate simulation parameters for the BASiCS simulation from a real dataset.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | BASiCSEstimate(counts, spike.info = NULL, batch = NULL, n = 20000,
thin = 10, burn = 5000, regression = TRUE,
params = newBASiCSParams(), verbose = TRUE, progress = TRUE, ...)
## S3 method for class 'SingleCellExperiment'
BASiCSEstimate(counts, spike.info = NULL,
batch = NULL, n = 20000, thin = 10, burn = 5000,
regression = TRUE, params = newBASiCSParams(), verbose = TRUE,
progress = TRUE, ...)
## S3 method for class 'matrix'
BASiCSEstimate(counts, spike.info = NULL,
batch = NULL, n = 20000, thin = 10, burn = 5000,
regression = TRUE, params = newBASiCSParams(), verbose = TRUE,
progress = TRUE, ...)
|
counts |
either a counts matrix or a SingleCellExperiment object containing count data to estimate parameters from. |
spike.info |
data.frame describing spike-ins with two columns: "Name"
giving the names of the spike-in features (must match
|
batch |
vector giving the batch that each cell belongs to. |
n |
total number of MCMC iterations. Must be |
thin |
thining period for the MCMC sampler. Must be |
burn |
burn-in period for the MCMC sampler. Must be in the range
|
regression |
logical. Whether to use regression to identify
over-dispersion. See |
params |
BASiCSParams object to store estimated values in. |
verbose |
logical. Whether to print progress messages. |
progress |
logical. Whether to print additional BASiCS progress messages. |
... |
Optional parameters passed to |
This function is just a wrapper around BASiCS_MCMC
that
takes the output and converts it to a BASiCSParams object. Either a set of
spike-ins or batch information (or both) must be supplied. If only batch
information is provided there must be at least two batches. See
BASiCS_MCMC
for details.
BASiCSParams object containing the estimated parameters.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## Not run:
# Load example data
library(scater)
data("sc_example_counts")
spike.info <- data.frame(Name = rownames(sc_example_counts)[1:10],
Input = rnorm(10, 500, 200),
stringsAsFactors = FALSE)
params <- BASiCSEstimate(sc_example_counts[1:100, 1:30],
spike.info)
params
## End(Not run)
|
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