title: Incorporating prior biologic information for high-dimensional rare variant association studies.
abstract: BACKGROUND
  Given the increasing scale of rare variant association studies, we introduce a method for high-dimensional studies that integrates multiple sources of data as well as allows for multiple region-specific risk indices.
  
  
  METHODS
  Our method builds upon the previous Bayesian risk index by integrating external biological variant-specific covariates to help guide the selection of associated variants and regions. Our extension also incorporates a second level of uncertainty as to which regions are associated with the outcome of interest.
  
  
  RESULTS
  Using a set of study-based simulations, we show that our approach leads to an increase in power to detect true associations in comparison to several commonly used alternatives. Additionally, the method provides multi-level inference at the pathway, region and variant levels.
  
  
  CONCLUSIONS
  To demonstrate the flexibility of the method to incorporate various types of information and the applicability to high-dimensional data, we apply our method to a single region within a candidate gene study of second primary breast cancer and to multiple regions within a candidate pathway study of colon cancer.
authors.affiliation: Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA.
authors.forename: Melanie A
authors.initials: MA
authors.lastname: Quintana
authors.forename: Fredrick R
authors.initials: FR
authors.lastname: Schumacher
authors.forename: Graham
authors.initials: G
authors.lastname: Casey
authors.forename: Jonine L
authors.initials: JL
authors.lastname: Bernstein
authors.forename: Li
authors.initials: L
authors.lastname: Li
authors.forename: David V
authors.initials: DV
authors.lastname: Conti
mesh_terms: D019313:BRCA1 Protein / Q000235:genetics*; D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000235:genetics*; D003110:Colonic Neoplasms / Q000235:genetics*; D003198:Computer Simulation; D004260:DNA Repair / Q000235:genetics; D005260:Female; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical
chemical_list: D019313:BRCA1 Protein; C492913:BRCA1 protein, human