RunGroupGSEA {CelliD} | R Documentation

## Run GSEA on cluster/groups

### Description

Calculate group gene specificty ranking and then perform geneset enrichment analysis on it.

### Usage

    RunGroupGSEA(
      X,
      pathways,
      group.by,
      reduction,
      dims,
      features,
      nperm,
      minSize,
      maxSize,
      gseaParam
    )

    ## S3 method for class 'Seurat'
    RunGroupGSEA(
      X,
      pathways,
      group.by = NULL,
      reduction = "mca",
      dims = seq(50),
      features = NULL,
      nperm = 1000,
      minSize = 10,
      maxSize = 500,
      gseaParam = 0
    )

    ## S3 method for class 'SingleCellExperiment'
    RunGroupGSEA(
      X,
      pathways,
      group.by,
      reduction = "MCA",
      dims = seq(50),
      features = NULL,
      nperm = 1000,
      minSize = 10,
      maxSize = 500,
      gseaParam = 0
    )

### Arguments

`X` | pathways List of gene sets to check
`pathways` | reduction Which dimensionality reduction to use, must be based on MCA.
`group.by` | dims A vector of integers indicating which dimensions to use with reduction embeddings and loadings for distance calculation.
`reduction` | features Character vector of feature names to subset feature coordinates. If not specified will take all features available from specified reduction Loadings.
`dims` | cells Character vector of cell names to subset cell coordinates. If not specified will take all features available from specified reduction Embeddings
`features` | cells Character vector of cell names to subset cell coordinates. If not specified will take all features available from specified reduction Embeddings
`nperm` | nperm Number of permutations to do. Minimial possible nominal p-value is about 1/nperm
`minSize` | minSize Minimal size of a gene set to test. All pathways below the threshold are excluded.
`maxSize` | maxSize Maximal size of a gene set to test. All pathways above the threshold are excluded.
`gseaParam` | gseaParam GSEA parameter value, all gene-level statis are raised to the power of 'gseaParam' before calculation of GSEA enrichment scores

### Value

A data.table with geneset enrichment analysis statistics.

### Examples

    seuratPbmc <- RunMCA(seuratPbmc, nmcs = 5)
    GSEAResults <- RunGroupGSEA(seuratPbmc, Hallmark, group.by = "seurat_clusters", dims = 1:5)

[Package CelliD version 1.2.1 Index]