celdaGridSearch {celda} | R Documentation

## Run Celda in parallel with multiple parameters

### Description

Run Celda with different combinations of parameters and multiple chains in parallel. The variable availableModels contains the potential models that can be utilized. Different parameters to be tested should be stored in a list and passed to the argument `paramsTest`. Fixed parameters to be used in all models, such as `sampleLabel`, can be passed as a list to the argument `paramsFixed`. When `verbose = TRUE`, output from each chain will be sent to a log file but not be displayed in `stdout`.

### Usage

    celdaGridSearch(x, ...)

    ## S4 method for signature 'SingleCellExperiment'
    celdaGridSearch(
      x,
      useAssay = "counts",
      altExpName = "featureSubset",
      model,
      paramsTest,
      paramsFixed = NULL,
      maxIter = 200,
      nchains = 3,
      cores = 1,
      bestOnly = TRUE,
      seed = 12345,
      perplexity = TRUE,
      verbose = TRUE,
      logfilePrefix = "Celda"
    )

    ## S4 method for signature 'matrix'
    celdaGridSearch(
      x,
      useAssay = "counts",
      altExpName = "featureSubset",
      model,
      paramsTest,
      paramsFixed = NULL,
      maxIter = 200,
      nchains = 3,
      cores = 1,
      bestOnly = TRUE,
      seed = 12345,
      perplexity = TRUE,
      verbose = TRUE,
      logfilePrefix = "Celda"
    )

### Arguments

`x` | A numeric matrix of counts or a SingleCellExperiment with the matrix located in the assay slot under `useAssay`. Rows represent features and columns represent cells.
`...` | Ignored. Placeholder to prevent check warning.
`useAssay` | A string specifying the name of the assay slot to use. Default "counts".
`altExpName` | The name for the altExp slot to use. Default "featureSubset".
`model` | Celda model. Options available in availableModels.
`paramsTest` | List. A list denoting the combinations of parameters to run in a celda model. For example, `list(K = seq(5, 10), L = seq(15, 20))` will run all combinations of K from 5 to 10 and L from 15 to 20 in model celda_CG.
`paramsFixed` | List. A list denoting additional parameters to use in each celda model. Default NULL.
`maxIter` | Integer. Maximum number of iterations of sampling to perform. Default 200.
`nchains` | Integer. Number of random cluster initializations. Default 3.
`cores` | Integer. The number of cores to use for parallel estimation of chains. Default 1.
`bestOnly` | Logical. Whether to return only the chain with the highest log likelihood per combination of parameters or return all chains. Default TRUE.
`seed` | Integer. Passed to with_seed. For reproducibility, a default value of 12345 is used. Seed values `seq(seed, (seed + nchains - 1))` will be supplied to each chain in `nchains`. If NULL, no calls to with_seed are made.
`perplexity` | Logical. Whether to calculate perplexity for each model. If FALSE, then perplexity can be calculated later with resamplePerplexity. Default TRUE.
`verbose` | Logical. Whether to print log messages during celda chain execution. Default TRUE.
`logfilePrefix` | Character. Prefix for log files from worker threads and main process. Default "Celda".

### Value

A SingleCellExperiment object. Function parameter settings and celda model results are stored in the metadata `"celda_grid_search"` slot.

### See Also

celda_G for feature clustering, celda_C for clustering of cells, and celda_CG for simultaneous clustering of features and cells. subsetCeldaList can subset the `celdaList` object. selectBestModel can get the best model for each combination of parameters.

### Examples

    ## Not run:
    data(celdaCGSim)
    ## Run various combinations of parameters with 'celdaGridSearch'
    celdaCGGridSearchRes <- celdaGridSearch(celdaCGSim$counts,
      model = "celda_CG",
      paramsTest = list(K = seq(4, 6), L = seq(9, 11)),
      paramsFixed = list(sampleLabel = celdaCGSim$sampleLabel),
      bestOnly = TRUE,
      nchains = 1,
      cores = 1)

    ## End(Not run)

[Package celda version 1.6.1 Index]