title: Integrated genome-wide pathway association analysis with INTERSNP.
abstract: OBJECTIVE
  Pathway association analysis (PAA) tests for an excess of moderately significant SNPs in genes from a common pathway.
  
  
  METHODS
  We present a Monte-Carlo simulation framework that allows to formulate the main ideas of existing PAA approaches using a self-contained rather than a competitive null hypothesis. A stand-alone implementation in INTERSNP makes time-consuming communication with standard GWAS software redundant. By additional parallelization with the OpenMP API, we achieve a reduction in running time for PAA by orders of magnitude, making a power simulation study for PAA feasible. Our approach properly accounts for linkage disequilibrium and is robust with respect to residual λ inﬂation.
  
  
  RESULTS
  We demonstrate that under simple, realistic disease models, PAA can actually strongly outperform the GWAS single-marker approach. PAA methods that make use of the strength of the SNP association (GenGen, Fisher's combination test), in general, perform better than ratio-based methods (ALIGATOR, SNP ratio), whereas the relative performance of gene-based scoring (ALIGATOR, GenGen) and pathway-based scoring (SNP ratio, Fisher's combination test) depends on the architecture of the assumed disease model. Finally, we present a new PAA score that models independent signals from the same gene in a regression framework and show that it is a reasonable compromise that combines the advantages of existing ideas.
authors.affiliation: German Center for Neurodegenerative Diseases (DZNE), University of Bonn, Bonn, Germany.
authors.forename: Christine
authors.initials: C
authors.lastname: Herold
authors.forename: Manuel
authors.initials: M
authors.lastname: Mattheisen
authors.forename: André
authors.initials: A
authors.lastname: Lacour
authors.forename: Tatsiana
authors.initials: T
authors.lastname: Vaitsiakhovich
authors.forename: Marina
authors.initials: M
authors.lastname: Angisch
authors.forename: Dmitriy
authors.initials: D
authors.lastname: Drichel
authors.forename: Tim
authors.initials: T
authors.lastname: Becker
mesh_terms: D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D009010:Monte Carlo Method; D020641:Polymorphism, Single Nucleotide; D012984:Software