Genomic Structural Equation Modelling (Genomic SEM) is a flexible statistical framework method for modeling the joint genetic architecture of constellations of genetically correlated traits and incorporating genetic covariance structure into multivariate GWAS discovery. Genomic SEM is applied to conventional GWAS summary statistics for the individual phenotypes of interest. It does not require raw data.

To get started using the GenomicSEM R package, follow this link: GenomicSEM wiki

To read the paper introducing Genomic SEM, follow these links: Paper Supplement(Text/Figures) Supplement(Tables)

A video overview of Genomic SEM can be found here: PGC Worldwide Lab Meeting

Subscribe to the Genomic SEM Users Google group here.

The full citation for the paper introducing Genomic SEM is:

Grotzinger, A. D., Rhemtulla, M., de Vlaming, R., Ritchie, S. J., Mallard, T. T.,  Hill, W. D, Ip, H. F., Marioni, R. E., McIntosh, A. M., Deary, I. J., Koellinger, P. D., Harden, K. P., Nivard, M. G., & Tucker-Drob, E. M. (2019). Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits. Nature Human Behaviour, 3, 513-525. [Nivard & Tucker-Drob jointly directed this work]