Hello SEQanswers community,
We're pleased to announce our upcoming live online course, Genomic Prediction of Complex Traits (GPCT01), designed for researchers working in statistical genomics, bioinformatics, quantitative genetics, and computational biology.
Genomic prediction has become an important tool for modelling complex traits from genome-wide marker data. This course provides a practical introduction to the statistical methods underpinning genomic prediction, including genomic relationship matrices, GBLUP, Bayesian approaches, model validation, and prediction accuracy. The emphasis is on understanding the methodology and implementing analyses in R using real genomic datasets.
Topics covered
- Foundations of genomic prediction and quantitative genetics
- Genomic relationship matrices (GRMs)
- Genomic Best Linear Unbiased Prediction (GBLUP)
- Bayesian genomic prediction models
- Estimation of marker effects
- Model training, validation, and cross-validation
- Assessing prediction accuracy and model performance
- Comparing genomic prediction methods
- Practical implementation in R
- Interpretation of genomic prediction results
The course is suitable for researchers working in:
- Bioinformatics
- Statistical genomics
- Computational biology
- Quantitative genetics
- Population and evolutionary genomics
- Plant and animal genomics
- Human genetics
- Any field involving genome-wide marker data and complex trait prediction
No prior experience with genomic prediction is required, although attendees should have a basic familiarity with R and genomic data analysis.
Course details
Course: Genomic Prediction of Complex Traits (GPCT01)
Format: Live online, instructor-led with practical coding sessions
Level: Intermediate
Further information, syllabus and registration:
Questions are very welcome.
[email protected]
Best,
Oliver Hooker
PR Stats
https://www.prstats.org