BASiCSEstimate {splatter} | R Documentation

## Estimate BASiCS simulation parameters

### Description

Estimate simulation parameters for the BASiCS simulation from a real dataset.

### Usage

    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, ...)

### Arguments

`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 `rownames(counts)`) and "Input" giving the number of input molecules.
`batch` | vector giving the batch that each cell belongs to.
`n` | total number of MCMC iterations. Must be `>= max(4, thin)` and a multiple of `thin`.
`thin` | thining period for the MCMC sampler. Must be `>= 2`.
`burn` | burn-in period for the MCMC sampler. Must be in the range `1 <= burn < n` and a multiple of `thin`.
`regression` | logical. Whether to use regression to identify over-dispersion. See `BASiCS_MCMC` for details.
`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 `BASiCS_MCMC`.

### Details

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.

### Value

BASiCSParams object containing the estimated parameters.

### Examples

    ## 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)

[Package splatter version 1.8.0 Index]