1. ‘Omics’ - Analysis of high dimensional Data
Achim Tresch Computational Biology

2. Topics Hypergeometric test [Khatri and Draghici 2005]
Kolmogorov-Smirnov test [Subramanian et al. 2005]

3. Gene Set Enrichment

4. Fisher‘s exact test, once more

5. Fisher‘s exact test, once more

6. Gene Ontology Example
559

7. (macromolecule biosynthesis)
Gene Ontology Example
(immune response)
(macromolecule biosynthesis)

8. Kolmogorov-Smirnov Test
< 10-10
Move 1/K up when you see a gene from group a
Move 1/(N-K) down when you see a gene not in group a

9. Topics

10. GO scoring: general problem

11. GO Independence Assumption
GO sets
light yellow

12. GO Independence Assumption
light yellow

13. The elim method

14. Top 10 significant nodes (boxes) obtained with the elim method

15. The weight method

16. The weight method

17. The weight method
(x)
(x)}

18. Top 10 significant nodes (boxes) obtained with the elim method
The weight method
Top 10 significant nodes (boxes) obtained with the elim method

19. Algorithms Summary

20. Topics

21. Significant GO terms in the ALL dataset
Top scoring GO term
Significant GO terms in the ALL dataset

22. Advantages & Disadvantages for ALL

23. Prostate cancer progression

24. Prostate cancer progression

25. Prostate cancer progression

26. Influence of the p-values adjustment

27. Simulation Study
Introduce noise

28. Simulation Study

29. Simulation Study

30. Quality of GO scoring methods
10% noise level
40% noise level

31. Summary

32. Adrian Alexa MPI Saarbrücken
Acknowledgements
Adrian Alexa MPI Saarbrücken