GetGroupGeneSet {CelliD} | R Documentation

## Extract cluster/group gene sets from MCA

### Description

Extract cluster/group gene sets from MCA

### Usage

    GetGroupGeneSet(X, group.by, reduction, dims, features, n.features)

    ## S3 method for class 'Seurat'
    GetGroupGeneSet(
      X,
      group.by = NULL,
      reduction = "mca",
      dims = seq(50),
      features = NULL,
      n.features = 200
    )

    ## S3 method for class 'SingleCellExperiment'
    GetGroupGeneSet(
      X,
      group.by = NULL,
      reduction = "MCA",
      dims = seq(50),
      features = NULL,
      n.features = 200
    )

### Arguments

`X` | Seurat or SingleCellExperiment object, alternatively a matrix.
`group.by` | column name of meta.data (Seurat) or ColData (SingleCellExperiment).
`reduction` | Which dimensionality reduction to use, must be based on MCA.
`dims` | A vector of integers indicating which dimensions to use with reduction for distance calculation.
`features` | A character vector of features name to subset feature coordinates for distance calculation.
`n.features` | A single integer specifying how many top features will be extracted from ranking.

### Value

Distance Matrix between groups (column) and genes (row)

### Examples

    seuratPbmc <- RunMCA(seuratPbmc, nmcs = 5)
    GroupGeneSet <- GetGroupGeneSet(seuratPbmc, dims = 1:5, group.by = "seurat_clusters")

[Package CelliD version 1.2.1 Index]