enrichment {eegc} | R Documentation

## Enrichment Analysis by Hypergeometric Distribution Test

### Description

Enrichment Analysis by Hypergeometric Distribution Test

### Usage

    enrichment(cate.gene, annotated.gene, background.gene, padjust.method = "fdr" )

### Arguments

`cate.gene` | a list of the five gene categories, alternatively output by `categorizeGene`.
`annotated.gene` | a list of annotated gene sets which the `cate.gene` are enriched in.
`background.gene` | vector of background genes, e.g. all genes screened by microarray or RNA-sequencing.
`padjust.method` | correction method for enrichment p-values, one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none", default to "fdr", see details in `p.adjust`.

### Value

A list of enrichment results for the five gene categories.

### Examples

    # load the cell/tissue-specific genes
    data(tissueGenes)
    # load the mapping file of cells/tissues to grouped cells/tissues
    data(tissueGroup)

    # get the background genes
    data(expr.filter)
    genes = rownames(expr.filter)
    # enrichment analysis for the five gene categories
    data(cate.gene)
    tissueenrich = enrichment(cate.gene = cate.gene, annotated.gene = tissueGenes,
                             background.gene = genes, padjust.method = "fdr")
    # select a group of cells/tissues
    tissueGroup.selec = c("stem cells","B cells","T cells","Myeloid","Endothelial CD105+")
    tissues.selec = tissueGroup[tissueGroup[,"Group"] %in% tissueGroup.selec,c(2,3)]
    # tissuetable = heatmapPlot(tissueenrich, terms = tissues.selec, GO=FALSE,
    #                           annotated_row = TRUE,annotation_legend = TRUE,
    #                           main = "Tissue-specific enrichment")

[Package eegc version 1.6.1 Index]