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Slide #1. Prospects for Identifying Functional Variation Across the Genome Slide #2. Why Study Complex Traits Slide #3. Why Dissect Complex Traits Slide #4. Outline Slide #5. = Slide #6. Cases Slide #7. Relationship between LD and Distance Slide #8. Using Linkage Disequilibrium to Dissect Complex Traits Slide #9. Using Linkage Disequilibrium to Dissect Complex Traits Slide #10. Features <BR> <BR>High power, even if carried out genome-wide (Risch and Merikangas) <BR> <BR>When people talk about the power of association studies they almost invariably talk about this design <BR> <BR>But this design is never carried out! Slide #11. Association Studies come in Two Flavors Slide #12. Outline Slide #13. We can simulate samples of gametes to estimate the power of association studies Slide #14. The Proportion of Association Studies for Which Slide #15. Three "easy" ways to improve the power of association studies <BR> <BR>Increase sample size <BR> <BR>Increase marker density <BR> <BR>Type the causative site (QTN) Slide #16. Typing the QTN increases power a great deal, increasing sample size and marker density are not as effective at increasing power Slide #17. Outline Slide #18. E(spl) - typical Drosophila gene density Slide #19. A fancy first pass algorithm for picking fSNPs Slide #20. Two Problems with Slide #21. How might a population geneticist identify functionally important non-coding regions? Slide #22. Deep Conservation Slide #23. Comparing Polymorphism to Divergence Slide #24. Population Subdivision Slide #25. Frequency Spectrum Skew / Abnormal LD Slide #26. Outline Slide #27. Our experiment Slide #28. Genes Examined Slide #29. What part of genes were sequenced? Slide #30. Slide 30 Slide #31. Slide 31 Slide #32. Results Slide #33. Neutral (12/26 genes) Slide #34. Neutral (12/26 genes) Slide #35. Sweep (3/26 genes) Slide #36. Balanced (3/26 genes) Slide #37. Fst (4/26 genes) Slide #38. Fst (4/26 genes) Slide #39. Conclusions