Gowinda

Gowinda performs unbiased gene set enrichment analysis for genome-wide association (GWA) studies by correcting sampling biases arising from single-nucleotide polymorphism (SNP) density, gene length, and gene overlap.

Key Features:

• Permutation tests: Uses permutation-based testing to correct for non-independence and unequal sampling probabilities of genes in GWA studies.
• Bias correction for gene length and overlap: Accounts for increased SNP counts in longer genes and clustering of overlapping genes during sampling.
• Gene Ontology (GO) focus: Targets Gene Ontology term enrichment while reducing artifacts specific to SNP-based mappings.
• False-positive reduction: Reduces the occurrence of false-positive GO terms resulting from unequal gene sampling.
• Statistical power: Maintains sufficient power to detect genuine enrichments despite bias corrections.
• Scalability: Employs multi-threading to perform millions of permutations for large datasets.
• Implementation: Implemented in Java 1.6.

Scientific Applications:

• GWA gene set enrichment: Analysis of gene set enrichment in genome-wide association (GWA) study results derived from SNP data.
• GO term interpretation: Identifying genuinely enriched Gene Ontology terms while minimizing bias-driven artifacts.
• Genetic association interpretation: Supporting interpretation of associations between genetic variation and phenotypic traits, complex biological processes, and disease mechanisms.

Methodology:

Performs permutation tests to correct for unequal gene sampling and non-independence, uses multi-threaded execution to run millions of permutations, and is implemented in Java 1.6.