runFeatureSelection {singleCellTK} | R Documentation

## Wrapper function to run all of the feature selection methods integrated within the singleCellTK package including three methods from Seurat ('vst', 'mean.var.plot' or 'dispersion') and the Scran 'modelGeneVar' method.

### Description

Wrapper function to run all of the feature selection methods integrated within the singleCellTK package including three methods from Seurat ('vst', 'mean.var.plot' or 'dispersion') and the Scran 'modelGeneVar' method.

### Usage

    runFeatureSelection(
      inSCE,
      useAssay,
      hvgMethod = c("vst", "mean.var.plot", "dispersion", "modelGeneVar")
    )

### Arguments

`inSCE` | Input `SingleCellExperiment` object.
`useAssay` | Specify the name of the assay that should be used. A normalized assay is recommended for use with this function.
`hvgMethod` | Specify the method to use for variable gene selection. Options include `"vst"`, `"mean.var.plot"` or `"dispersion"` from Seurat and `"modelGeneVar"` from Scran.

### Value

A `SingleCellExperiment` object that contains the computed statistics in the `rowData` slot of the output object. This function does not return the names of the variable features but only computes the statistics that are stored in the `rowData` slot of the. To get the names of the variable features `getTopHVG` function should be used after computing these statistics.

### Examples

    data("mouseBrainSubsetSCE", package = "singleCellTK")
    mouseBrainSubsetSCE <- runFeatureSelection(mouseBrainSubsetSCE,
                                               "logcounts",
                                               "modelGeneVar")

[Package singleCellTK version 2.2.0 Index]