AG2PI Workshop #26 - Friday May 17, 2024
Combined GWAS and TWAS using SVEN
Friday May 17, 2024
10:00 AM - 1:00 PM
(US Central Time)
Purpose
Hands-on training in combined GWAS and TWAS using SVEN from R package bravo.
Registration
Register for the virtual event by clicking the link below. Upon registration, you will receive a confirmation email with information about joining the meeting
Workshop RegistrationA recording of this event will be available at a later date
Genomewide association studies (GWAS) and transcriptomewide association studies (TWAS) help understand the genetic bases of phenotypic variation in species. Although GWAS and TWAS results can be combined using Fisher's Combined Test, the statistical power to detect causal genes could be increased by combining GWAS and TWAS through a single model. This workshop aims to equip you with a tool for combining GWAS and TWAS using a hierarchical Bayesian method called SVEN. In addition to computational scalability, SVEN comes with the theoretical guarantee that both the false negative and the false positive rates converge to zero with increasing sample size.
- Fundamental of Bayesian hierarchical models in association studies
- Demonstration of SVEN from R package bravo using data from a maize panel
- Hands-on experience in using SVEN under the R statistical software
- Understand the marginal inclusion probability as an alternative to the p-value
- Use SVEN to analyze your dataset
- Summarize and visualize the output from SVEN
Workshop Schedule
About Presenters
Dr. Somak Dutta is an Associate Professor of Statistics at Iowa State University. He received his Ph.D. in Statistics from the University of Chicago. His research interests include developing theory, methods, and matrix-free computations for high-dimensional problems..
Dr. Vivekananda Roy is a faculty member in the Department of Statistics at Iowa State University. Currently, he is serving three statistics journals---Electronic Journal of Statistics, Journal of Computational and Graphical Statistics and Sankhya, Series B as an associate editor. His research interests are Markov chain Monte Carlo, importance sampling, high dimensional data analysis and model selection.
