xina_enrichment {XINA} | R Documentation

## xina_enrichment

### Description

xina_enrichment conducts functional enrichment tests using gene ontology or KEGG pathway terms for a given protein list

### Usage

    xina_enrichment(string_db, protein_list, enrichment_type = "GO",
      pval_threshold = 0.05, methodMT = "fdr")

### Arguments

`string_db` | STRINGdb object
`protein_list` | A vector of gene names to draw protein-protein interaction network.
`enrichment_type` | A functional annotation for the enrichment test. 'enrichment_type' should be one of 'GO' and 'KEGG',
`pval_threshold` | P-value threshold to get significantly enriched terms from the given proteins
`methodMT` | Method for p-value adjustment. See get_enrichment. Default is 'fdr'.

### Value

A list of data frames containing enrichment results

### Examples

    ## Not run:
    library(STRINGdb)
    library(Biobase)

    # load XINA example data
    data(xina_example)

    # Get STRING database for protein-protein intereaction information
    string_db <- STRINGdb$new( version="10", species=9606, score_threshold=0, input_directory="" )
    string_db

    # XINA analysis with STRING DB
    xina_result <- xina_analysis(example_clusters, string_db)

    # Select proteins that showed cluster #1 in the Stimulus2 condition
    subgroup <- subset(example_clusters$aligned, Stimulus2==1)
    protein_list <- as.vector(subgroup$`Gene name`)

    # Enrichment test using KEGG pathway terms that have adjuseted p-value less than 0.1
    kegg_enriched <- xina_enrichment(string_db, protein_list,
    enrichment_type = "KEGG", pval_threshold=0.1)
    plot_enrichment_results(kegg_enriched$KEGG, num_terms=10)

    # Enrichment test using GO terms that have adjuseted p-value less than 0.1
    go_enriched <- xina_enrichment(string_db, protein_list,
    enrichment_type = "GO", pval_threshold=0.1)
    plot_enrichment_results(go_enriched$Component, num_terms=10)

    ## End(Not run)

[Package XINA version 1.6.0 Index]