💼 Modern Programming in Genomic Prediction
June 24 - 28, 2019, Meyer Hall, University of California, Davis
- Instructors:
- Dr. Rohan Fernando, Iowa State University
- Dr. Hao Cheng, University of California, Davis
- Topics:
- Learn to code for genomic prediction from scratch. The following topics will be covered:
- Mixed effects models with polygenic, maternal and permanent environment effects
- Use of pedigree information
- Iterative methods for solving linear systems, e.g, Jocobi, ‎Gauss–Seidel
- GBLUP and Bayesian alphabet
- Variance component estimation
- Single-step methods
- The workshop will provide an introduction to the programming language Julia and how to use it to code algorithms listed above from scratch. The course consists of lectures and practical components with hands-on exercises.
- Attendance:
- The attendance is limited to 30 to preserve a high TA-to-student ratio of 1:6 to offer more personalized instruction and feedback.
- Prerequisites:
- Knowledge of quantitative genetics
- Familiar with mixed effects models
- Prior programming knowledge
- Fees:
- Industry - $400
- Academic - $300
- Graduate student - $150
- Registration:
- Logistics:
- Housing:
- Davis:
- Special requirements:
- Please email [email protected] if you have any special requirements (e.g., registration, lodging, visa, invitation letters, international travel).
- What do people say about this workshop?
I really like that we get to build our own package 'miniJWAS' from scratch. This actually helps me understand the complexity underlying other public packages/software out there much better. I'm not saying I understand 100% of what we went over in the past week, but I enjoy it and feel quite proud to have come this far!
I love this workshop!!!!!!
I want to participate in the same course once more.
The course instructors are incredibly compassionate, positive, and supportive.
I like TAs most. They are willing to help you and patient. Also, they understand the material well so their explanation are easy to understand.
It is interesting and relevant to many parts of breeding, and hands on coding is always the best way to learn how to best use a program.
I learnt a very efficient language and in the process, learnt the programming of mixed linear model. Every topic is very well integrated with both learning goals.