TILJ5103 STAT1: Statistics of Genome-wide Association Studies (JSS30) (2 cr)
Pass - fail
Faculty of Mathematics and Science
- Statistical concepts in genome-wide analyses: From significance and power to probability of association.
- Genetic population structure, confounders and covariates.
- Statistical fine-mapping via variable selection.
- Most recent methods for biobank-scale data sets including linear and logistic mixed models for 10^5 individuals x 10^7 genetic variants x 10^3 outcome measurements.
By the end of the course, the student:
- understands the statistical inference framework for genome-wide data analysis: how to quantify uncertainty and what are common sources of biases.
- is able to utilize the statistical summaries of genome-wide analyses in downstream analyses such as fine-mapping.
- is aware of most recent approaches available for genome-wide analyses of biobank-scale data sets.
Description of prerequisites
Basic level familiarity with the R software, with linear regression and with statistical inference.
Select all marked parts
Parts of the completion methods
Participation in teaching (2 cr)
Participation in teaching
Pass - fail
No published teaching
Participation in the lectures and exercise work with R software to be returned after the course