Description Usage Arguments Details Value Examples
View source: R/BASiCS-estimate.R
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 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | 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)
set.seed(1)
sce <- mockSCE()
spike.info <- data.frame(Name = rownames(sce)[1:10],
Input = rnorm(10, 500, 200),
stringsAsFactors = FALSE)
params <- BASiCSEstimate(sce[1:100, 1:30], spike.info)
params
## End(Not run)
|
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