5. SNPedia The SNPedia website http://www.snpedia.com/index.php/SNPedia A thank you from SNPedia http://snpedia.blogspot.com/2012/12/o-come-all-ye-faithful.html Class website for SNPedia http://stanford.edu/class/gene210/web/html/projects.html List of last years write-ups http://stanford.edu/class/gene210/archive/2012/projects_2012.html How to write up a SNPedia entry http://stanford.edu/class/gene210/web/html/snpedia.html

6. Ancestry/Height Go to Genotation, Ancestry, PCA (principle components analysis) Load in genome. Start with HGDP world Resolution 10,000 PC1 and PC2 Then go to Ancestry, painting

7. Ancestry Analysis people 1 10,000 SNPs 1 1M AA CC etc GG TT etc AG CT etc We want to simplify this 10,000 people x 1M SNP matrix using a method called Principle Component Analysis.

8. PCA example students 1 30 Eye color Lactose intolerant Asparagus Ear Wax Bitter taste Sex Height Weight Hair color Shirt Color Favorite Color Etc. 100 Kinds of students Body types simplify

9. Informative traits Skin color eye color height weight sex hair length etc. Uninformative traits shirt color Pants color favorite toothpaste favorite color etc. ~SNPs informative for ancestry ~SNPs not informative for ancestry

10. PCA example Skin Color Eye color Lactose intolerant Asparagus Ear Wax Bitter taste Sex Height Weight Pant size Shirt size Hair color Shirt Color Favorite Color Etc. 100 Skin color Eye color Hair color Lactose intolerant Ear Wax Bitter taste Sex Height Weight Pant size Shirt size Asparagus Shirt Color Favorite Color Etc. 100 RACE Bitter taste SIZE Asparagus Shirt Color Favorite Color Etc. 100

11. PCA example Skin color Eye color Hair color Lactose intolerant Ear Wax Bitter taste Sex Height Weight Pant size Shirt size Asparagus Shirt Color Favorite Color Etc. 100 RACE Bitter taste SIZE Asparagus Shirt Color Favorite Color Etc. 100 Size = Sex + Height + Weight + Pant size + Shirt size …

12. Ancestry Analysis 1234567 Snp1AAAAAAT Snp2GGGGGGG Snp3AAAAAAT Snp4CCCTTTT Snp5AAAAAAG Snp6GGGAAAA Snp7CCCCCCA Snp8TTTGGGG Snp9GGGGGGT Snp10AGCTAGC Snp11TTTTTTC Snp12GCTAAGC

13. Reorder the SNPs 1234567 Snp1AAAAAAT Snp3AAAAAAT Snp5AAAAAAG Snp7CCCCCCA Snp9GGGGGGT Snp11TTTTTTC Snp2GGGGGGG Snp4CCCTTTT Snp6GGGAAAA Snp8TTTGGGG Snp10AGCTAGC Snp12GCTAAGC

14. Ancestry Analysis 1234567 Snp1AAAAAAT Snp3AAAAAAT Snp5AAAAAAG Snp7CCCCCCA Snp9GGGGGGT Snp11TTTTTTC Snp4CCCTTTT Snp6GGGAAAA Snp8TTTGGGG Snp2GGGGGGG Snp10AGCTAGC Snp12GCTAAGC

15. Ancestry Analysis 1234567 Snp1AAAAAAT Snp3AAAAAAT Snp5AAAAAAG Snp7CCCCCCA Snp9GGGGGGT Snp11TTTTTTC 1-67 Snp1AT Snp3AT Snp5AG Snp7CA Snp9GT Snp11TC 1 Snp1A Snp3A Snp5A Snp7C Snp9G Snp11T 7 Snp1T Snp3T Snp5G Snp7A Snp9T Snp11C =X =x

16. Ancestry Analysis 1234567 Snp1AAAAAAT Snp3AAAAAAT Snp5AAAAAAG Snp7CCCCCCA Snp9GGGGGGT Snp11TTTTTTC MN PC1Xx

17. Ancestry Analysis 1234567 Snp4CCCTTTT Snp6GGGAAAA Snp8TTTGGGG 1-34-7 Snp4CT Snp6GA Snp8TG 1-3 Snp4C Snp6G Snp8T 4-7 Snp4T Snp6A Snp8G 1-34-7 PC2Yy =Y =y

18. Ancestry Analysis 1234567 PC1XXXXXXx PC2YYYyyyy Snp2GGGGGGG Snp10AGCTAGC Snp12GCTAAGC 1-34-67 PC1XXx PC2Yyy Snp2 Snp10 Snp12

19. PC1 and PC2 inform about ancestry 1-34-67 PC1XXx PC2Yyy Snp2GGG Snp10ATC Snp12GAC

21. Chromosome painting Jpn x CEUCEU x CEU fathermother Stephanie Zimmerman x

22. Complex traits: height heritability is 80% NATURE GENETICS | VOLUME 40 | NUMBER 5 | MAY 2008

23. NATURE GENETICS VOLUME 40 [ NUMBER 5 [ MAY 2008 Nature Genetics VOLUME 42 | NUMBER 11 | NOVEMBER 2010 63K people 54 loci ~5% variance explained.

24. Calculating RISK for complex traits Start with your population prior for T2D: for CEU men, we use 0.237 (corresponding to LR of 0.237 / (1 – 0.237) = 0.311). Then, each variant has a likelihood ratio which we adjust the odds by. Slide by Rob Tirrell, 2010

25. 832 | NATURE | VOL 467 | 14 OCTOBER 2010 183K people 180 loci ~10% variance explained

26. Missing Heritability

27. Where is the missing heritability? Lots of minor loci Rare alleles in a small number of loci Gene-gene interactions Gene-environment interactions

28. Nature Genetics VOLUME 42 | NUMBER 7 | JULY 2010

30. This approach explains 45% variance in height. Q-Q plot for human height

31. Rare alleles 1.You wont see the rare alleles unless you sequence 2.Each allele appears once, so need to aggregate alleles in the same gene in order to do statistics. CasesControls

32. Gene-Gene ABC DEF diabetes A - not affected D - not affected A - D - affected A - E - affected A - F - affected A - B - not affected D - E - not affected

33. Gene-environment 1.Height gene that requires eating meat 2.Lactase gene that requires drinking milk These are SNPs that have effects only under certain environmental conditions