1. Classification and risk prediction Usman Roshan

2. Disease risk prediction What is the best method to predict disease risk? –We looked at the maximum likelihood estimator for Gaussian last time –Before that we looked at the composite odds ratio score –Today we look at the support vector machine

3. Discriminative learning No assumptions about the underlying model Support vector machine: optimally separating hyperplane between two sets of points

4. Support vector machine: optimally separating hyperplane

5. SVMs

6. How to find w and w 0 for SVM? SVM gives a contrained optimization problem Solve by the KKT theorem (extension of Lagrange multipliers) Plenty of SVM software out there. Two popular packages: –SVM-light –LIBSVM

7. Disease risk prediction with SVMs and composite odds ratio score Randomly select 90% of data to be training and 10% to be test from WTCCC datasets. Learn odds ratios and SVM classifier from training data Compute ROC area under curve on test data Repeat this five times and plot average ROC area under curve But which SNPs do we select?

8. Type 1 diabetes

9. Arthritis

10. Crohn’s disease

11. Type 2 diabetes