geneSetEnrich {celda} | R Documentation

## Gene set enrichment

### Description

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

### Usage

    geneSetEnrich(counts, celdaModel, databases, fdr = 0.05)

### Arguments

`counts` | Integer count matrix. Rows represent genes and columns represent cells. Row names of the matrix should be gene names.
`celdaModel` | Celda object of class 'celda_G' or 'celda_CG'.
`databases` | Character vector. Name of reference database. Available databases can be viewed by running `enrichR::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

### Examples

    library(M3DExampleData)
    counts <- M3DExampleData::Mmus_example_list$data
    #subset 100 genes for fast clustering
    counts <- counts[1500:2000, ]
    #cluster genes into 10 modules for quick demo
    cm <- celda_G(counts = as.matrix(counts), L = 10, verbose = FALSE)
    gse <- geneSetEnrich(counts,
        cm,
        databases = c('GO_Biological_Process_2018','GO_Molecular_Function_2018'))

[Package celda version 1.0.4 Index]