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Run Gene Enrichment and Compare with TKOI Data

run_gene_enrichment.Rd

This function performs gene enrichment analysis using the clusterProfiler package and integrates the results with the tKOIList object, specifically comparing the enrichment results with the TKOI data. It generates scatter plots visualizing the relationship between TKOI scores and enrichment results.

Usage

run_gene_enrichment(tkoi_list)

Arguments

tkoi_list

An object of class tKOIList that contains the input data for analysis. The object should include the following slots:

  • expression_data: A data.frame with columns including gene_name and pvalue.

  • network_summary_statistics: A list containing network-level summary data for Biological Process (BP), Cellular Component (CC), and Molecular Function (MF), each stored as a data.frame.

  • pvalue_threshold: A numeric value specifying the significance threshold for filtering genes.

Value

A tKOIList object with the gene_enrichment_comparison slot populated. This slot is a list containing:

  • enrichment_result: A data.frame with the merged results of the enrichment analysis and TKOI network data.

  • comparison_scatter1: A ggplot object visualizing a scatter plot without facets.

  • comparison_scatter2: A ggplot object visualizing a scatter plot with facets for each namespace.

Details

The function performs the following steps:

  1. Extracts genes with p-values below the threshold specified in the tkoi_list.

  2. Conducts Gene Ontology (GO) enrichment analysis for Biological Process (BP), Cellular Component (CC), and Molecular Function (MF) using clusterProfiler::enrichGO.

  3. Computes pairwise term similarities using enrichplot::pairwise_termsim.

  4. Merges the enrichment results with TKOI network statistics to create a unified dataset.

  5. Generates scatter plots to visualize the relationship between TKOI network enrichment effect size and gene enrichment q-values.

Examples

if (FALSE) { # \dontrun{
# Example usage of the function
library(clusterProfiler)
library(enrichplot)
library(org.Hs.eg.db)
library(ggplot2)
library(dplyr)

# Create a dummy tKOIList object
tkoi_list <- new("tKOIList",
                 expression_data = data.frame(
                   gene_name = c("gene1", "gene2", "gene3"),
                   pvalue = c(0.01, 0.02, 0.2)
                 ),
                 network_summary_statistics = list(
                   BiologicalProcess = data.frame(
                     identifier = c("GO:0008150", "GO:0009987"),
                     node_id = c(1, 2),
                     pagerank = c(0.2, 0.3),
                     beta = c(0.5, 0.4),
                     p_value = c(0.01, 0.02),
                     fdr = c(0.05, 0.1),
                     definition = c("process1", "process2")
                   ),
                   CellularComponent = data.frame(),
                   MolecularFunction = data.frame()
                 ))

# Run the enrichment function
result <- run_gene_enrichment(tkoi_list)
} # }