snpGeneSets: An R Package for Genome-Wide Study Annotation

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Genome-wide studies (GWS) generate vast amounts of single nucleotide polymorphism (SNP) association and gene expression data.
• Interpreting these large-scale genomic results necessitates computationally intensive annotation and downstream analysis.
• Next-generation sequencing technologies have further increased the volume of identified genetic variants and genes.

Purpose of the Study:

• To develop and present the snpGeneSets R package for simplifying the annotation and analysis of GWS results.
• To provide efficient tools for mapping genomic data, linking SNPs to genes, and performing gene set enrichment analyses.
• To facilitate the interpretation of complex genomic findings through integrated knowledge bases and wrapper functions.

Main Methods:

• The snpGeneSets package integrates local knowledge bases for SNPs, genes, and gene sets.
• It utilizes R language wrapper functions for transparent and efficient access to low-level databases.
• Key functions include genomic mapping, bidirectional SNP-gene and gene-gene set mapping, gene effect calculation, and gene set enrichment analysis.

Main Results:

• The package successfully annotated and performed enrichment analysis on genome-wide association study (GWAS) and genome-wide expression study (GWES) data for type 2 diabetes.
• Demonstrated the utility of snpGeneSets in handling large genomic datasets and identifying functional pathways.
• The package offers open-source, free access to advanced bioinformatics tools.

Conclusions:

• snpGeneSets effectively simplifies the complex tasks of annotating and analyzing genome-wide study results.
• The package is a valuable tool for researchers investigating genetic associations and pathways in complex diseases.
• Its open-source nature promotes accessibility and further development within the bioinformatics community.