1. Applying haplotype models to association study design Natalie Castellana June 7, 2005

2. Background Certain characteristics are linked to genetic factors. By finding models for genetic variation, we can determine which genes render an individual susceptible to a certain disease.

3. Normal Allele Mutant allele 1000011010110100000010 Background(2) SNP Haplotype Association Test Given that this sample has haplotype 01101, does it have the disease?

4. …1110101… …1000011… Genetic Variation Mutation: …1000001… Recombination: …1110011… …1000101… …1001001… Because of recombination, similar genetic variation can be found within closely linked regions.

5. Generating Data Generate genetic segments Isolate the disease causing allele, and segregate the case (diseased) samples from the control (healthy) samples. …1 0 1 1 1 0 1 1 1 1… …1 1 1 0 0 1 1 0 1 0 … …0 0 1 1 0 0 1 1 0 1… …1 0 1 0 1 1 0 0 1 0… ControlCase

6. Testing individual SNP’s Go through each SNP and determine which SNP’s accurately predict which samples have the disease and which do not. Case Control 10 11…..010 0… 01 10......100 1…

7. Haplotype block method Instead of looking at each individual SNP, we can look at groups of contiguous SNP’s. 1101000000…11… 1101100100…01… 0111000000…10… 1101100100…00…

8. Blocks vs. SNP’s

9. Haplotype motif method Notion that a sequence is the concatenation of segments (like the block method) but does not require conservation of boundaries. 1101000000… 1100100100… 0111000000… 1101100111…

10. Approximation Algorithm General idea: …1 0 0 0 1 ………………………………… cccccccc Pick the best partition, minimizing the number of motifs needed to explain all the data.

11. Finding Motifs C 0 1 1 0 1 0 0 1 1 0 0 0 1 1 0 0 1 000…000 000..100 0 1 ……… 111…111

12. What I am working on Implementing an efficient algorithm for finding motifs. Performing association tests on the SNP, block, and motif models.