title: Identification of causal genes for complex traits.
abstract: BACKGROUND
  Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations.
  
  
  RESULTS
  In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2.
  
  
  METHODS
  Software is freely available for download at genetics.cs.ucla.edu/caviar.
authors.affiliation: Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA.
authors.forename: Farhad
authors.initials: F
authors.lastname: Hormozdiari
authors.affiliation: Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA.
authors.forename: Gleb
authors.initials: G
authors.lastname: Kichaev
authors.affiliation: Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA.
authors.forename: Wen-Yun
authors.initials: WY
authors.lastname: Yang
authors.affiliation: Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA.
authors.forename: Bogdan
authors.initials: B
authors.lastname: Pasaniuc
authors.affiliation: Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA Department of Computer Science, Inter-Departmental Program in Bioinformatics, Department of Human Genetics and Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA 90095, USA.
authors.forename: Eleazar
authors.initials: E
authors.lastname: Eskin
mesh_terms: D000465:Algorithms; D000818:Animals; D016633:Apolipoprotein A-II / Q000235:genetics; D003627:Data Interpretation, Statistical; D005796:Genes; D055106:Genome-Wide Association Study; D006801:Humans; D015810:Linkage Disequilibrium; D051379:Mice; D020641:Polymorphism, Single Nucleotide
chemical_list: D016633:Apolipoprotein A-II