Using Genomic SEM for Multivariate GWAS Discovery


A powerful application of Genomic Structural Equation Modeling (Genomic SEM) is to specify a model in which the SNP effects occur at the level of a latent genetic factor defined by several phenotypes. This allows researchers... [ view full abstract ]


  1. Andrew Grotzinger (University of Texas at Austin)
  2. Mijke Rhemtulla (University of California, Davis)
  3. Ronald de Vlaming (Vrije Universiteit Amsterdam)
  4. Stuart Ritchie (University of Edinburgh)
  5. Travis Mallard (University of Texas at Austin)
  6. W. David Hill (University of Edinburgh)
  7. Hill Ip (Department of Biological Psychology, VU University)
  8. Andrew Mcintosh (Edi)
  9. Ian Deary (University of Edinburgh)
  10. Philipp Koellinger (Vrije Universiteit Amsterdam)
  11. K. Paige Harden (University of Texas at Austin)
  12. Michel Nivard (Department of Biological Psychology, VU University)
  13. Elliot M. Tucker-Drob (University of Texas at Austin)

Topic Areas

Gene Finding Strategies , Psychopathology (e.g., Internalizing, Externalizing, Psychosis) , Statistical Methods


SY-5A » Genomic Structural Equation Modeling Provides Insights into the Multivariate Genetic Architecture of Complex Traits (10:30 - Friday, 22nd June, Auditorium)

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