Complex Trait Genomic Analysis is complex and there are no simple answers to complex issues. You are usually forced to remain in the probability grey area when making inferences. This does not mean you cannot make any assertion nor gain any knowledge, simply that assertions do narrow your ignorance but they do not remove it.
Most genes that are of socioeconomic importance, e.g., genes affecting stress resistance in plants or that makes Iberian pig meat taste good, are very difficult to find because they are influenced by many genes of small effect. These notes deal with concepts and statistical and computational tools that help us to identify these genes. More importantly, these tools can be used as well to utilize genetic variability for improvement, even if the specific genes are unknown, a method called Genomic Prediction.
So far, the course is organized as follows:
- Background
- Genome Wide Association Studies (GWAS
- Genomic Prediction
- Next Generation Sequence data analysis
- Machine Learning
Not all chapters are equally well developed, especially the machine learning one is just a draft.
This course was first taught in wonderful Salvador de Bahia in November 2018 thanks to my good friend and former student Luis Fernando Batista, from UFBA.
