R: Gene set enrichment

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 1.3.4 Index]