title: Comparison of methods for competitive tests of pathway analysis.
abstract: It has been suggested that pathway analysis can complement single-SNP analysis in exploring genomewide association data. Pathway analysis incorporates the available biological knowledge of genes and SNPs and is expected to improve the chances of revealing the underlying genetic architecture of complex traits. Methods for pathway analysis can be classified as competitive (enrichment) or self-contained (association) according to the hypothesis tested. Although association tests are statistically more powerful than enrichment tests they can be difficult to calibrate because biases in analysis accumulate across multiple SNPs or genes. Furthermore, enrichment tests can be more scientifically relevant than association tests, as they detect pathways with relatively more evidence for association than the remaining genes. Here we show how some well known association tests can be simply adapted to test for enrichment, and compare their performance to some established enrichment tests. We propose versions of the Adaptive Rank Truncated Product (ARTP), Tail Strength Measure and Fisher's combination of p-values for testing the enrichment null hypothesis. We compare the behaviour of these proposed methods with the established Hypergeometric Test and Gene-Set Enrichment Analysis (GSEA). The results of the simulation study show that the modified version of the ARTP method has generally the best performance across the situations considered. The methods were also applied for finding enriched pathways for body mass index (BMI) and platelet function phenotypes. The pathway analysis of BMI identified the Vasoactive Intestinal Peptide pathway as significantly associated with BMI. This pathway has been previously reported as associated with BMI and the risk of obesity. The ARTP method was the method that identified the largest number of enriched pathways across all tested pathway databases and phenotypes. The simulation and data application results are in agreement with previous work on association tests and suggests that the ARTP should be preferred for both enrichment and association testing.
authors.affiliation: Medical Research Council Biostatistics Unit, Institute of Public Health, Cambridge, United Kingdom.
authors.forename: Marina
authors.initials: M
authors.lastname: Evangelou
authors.forename: Augusto
authors.initials: A
authors.lastname: Rendon
authors.forename: Willem H
authors.initials: WH
authors.lastname: Ouwehand
authors.forename: Lorenz
authors.initials: L
authors.lastname: Wernisch
authors.forename: Frank
authors.initials: F
authors.lastname: Dudbridge
mesh_terms: D000465:Algorithms; D001792:Blood Platelets / Q000378:metabolism / Q000502:physiology; D015992:Body Mass Index; D003198:Computer Simulation; D055106:Genome-Wide Association Study; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008957:Models, Genetic; D058977:Molecular Sequence Annotation; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide