geneSetEnrich {celda} | R Documentation

## Gene set enrichment

### Description

Identify and return significantly-enriched terms for each gene module in a Celda object or a SingleCellExperiment object. Performs gene set enrichment analysis for Celda identified modules using the enrichr.

### Usage

    geneSetEnrich(
      x,
      celdaModel,
      useAssay = "counts",
      altExpName = "featureSubset",
      databases,
      fdr = 0.05
    )

    ## S4 method for signature 'SingleCellExperiment'
    geneSetEnrich(
      x,
      useAssay = "counts",
      altExpName = "featureSubset",
      databases,
      fdr = 0.05
    )

    ## S4 method for signature 'matrix'
    geneSetEnrich(x, celdaModel, databases, fdr = 0.05)

### 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. Rownames of the matrix or SingleCellExperiment object should be gene names.
`celdaModel` | Celda object of class `celda_G` or `celda_CG`.
`useAssay` | A string specifying which assay slot to use if `x` is a SingleCellExperiment object. Default "counts".
`altExpName` | The name for the altExp slot to use. Default "featureSubset".
`databases` | Character vector. Name of reference database. Available databases can be viewed by listEnrichrDbs.
`fdr` | False discovery rate (FDR). Numeric. Cutoff value for adjusted p-value, terms with FDR below this value are considered significantly enriched.

### Value

List of length 'L' where each member contains the significantly enriched terms for the corresponding module.

### Author(s)

Ahmed Youssef, Zhe Wang

### Examples

    library(M3DExampleData)
    counts <- M3DExampleData::Mmus_example_list$data
    # subset 500 genes for fast clustering
    counts <- counts[seq(1501, 2000), ]
    # cluster genes into 10 modules for quick demo
    sce <- celda_G(x = as.matrix(counts), L = 10, verbose = FALSE)
    gse <- geneSetEnrich(sce,
      databases = c("GO_Biological_Process_2018", "GO_Molecular_Function_2018"))

[Package celda version 1.8.1 Index]