GetGroupGeneRanking {CelliD} | R Documentation

## Gene Specificity Ranking Calculation

### Description

Gene Specificity Ranking Calculation

### Usage

    GetGroupGeneRanking(X, group.by, reduction, dims, features)

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

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

### 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 embeddings and loadings for distance calculation.
`features` | A character vector of features name to subset feature coordinates for distance calculation.

### Value

List of genes ranking for each groups

### Examples

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

[Package CelliD version 1.2.1 Index]