CAVIAR (CAusal Variants Identication in Associated Regions), a statistical framework that quantifies the probability of each variant to be causal while allowing with arbitrary number of causal variants.
eCAVIAR (eQTL and GWAS CAusal Variants Identification in Associated Regions), a statistical framework that quantifies the probability of the variant to be causal both in GWAS and eQTL studies, while allowing with arbitrary number of causal variants.
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Farhad Hormozdiari, Ayellet V. Segre, Martijn van de Bunt, Xiao Li, Jong Wha J Joo, Michael Bilow, Jae Hoon Sul, Bogdan Pasaniuc and Eleazar Eski. Joint Fine Mapping of GWAS and eQTL Detects Target Gene and Relevant Tissue.
Farhad Hormozdiari, Emrah Kostem, Eun Yong Kang, Bogdan Pasaniuc and Eleazar Eskin. Identifying Causal Variants at Loci with Multiple Signals of Association. Genetics, 44, 725–731 (2014). Read more.
For specific questions or bug report about CAVIAR software, please email Farhad Hormozdiari (fhormoz (AT) cs.ucla.edu).
F.H., E.K., E.Y.K., and E.E. are supported by National Science Foundation (NSF) grants 0513612, 0731455, 0729049, 0916676, 1065276,1302448, and 1320589 and National Institutes of Health (NIH) grants K25- HL080079, U01-DA024417, P01-HL30568, P01-HL28481, R01-GM083198, R01-MH101782 and R01-ES022282. We acknowledge the support of the NINDS Informatics Center for Neurogenetics and Neurogenomics (P30 NS062691). B.P is supported in part by the National Institutes of Health (R03 CA162200 and R01 GM053275).