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Gene Hunting: Design and statistics

Gene Hunting: Design and statistics. Genotype:. AA. AC. CC. Schiz:. Phenotype:. Not Schiz:. Population- based Association Design: Qualitative Phenotype. Do c 2 test for association. Population- based Association Design: Quantitative Phenotype. Phenotype. 0 (AA). 1 (AC). 2 (CC).

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Gene Hunting: Design and statistics

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  1. Gene Hunting:Design and statistics

  2. Genotype: AA AC CC Schiz: Phenotype: Not Schiz: Population-basedAssociation Design:Qualitative Phenotype Do c2 test for association.

  3. Population-basedAssociation Design:Quantitative Phenotype Phenotype 0(AA) 1(AC) 2(CC) Number of C alleles Compute the correlation (or regression slope)

  4. GWAS: Genome-wideAssociation Study DNA arrays with 1,000s of SNPs scattered throughout the genome. (Current chips in 2009 has over 1,000, 000 different SNPs) Select the SNPs so that they cover ALL the genome using haplotype blocks. (Some DNA chips oversample SNPs in protein coding regions) Genotype patients and controls on all the SNPs(or genotype a random sample of the population). Find the SNPs that differ patients from controls (or have a significant correlation with a quantitative phenotype). Problem: number of statistical tests.

  5. GWAS results as of 2012 From http://www.genome.gov/multimedia/illustrations/GWAS_2012-12.pdf

  6. GWAS and Quantitative Phenotype:Height (Weedon et al, 2007) Note: Effect size = c. 0.2 inches, length of a housefly

  7. Problems with GWAS (1) Expensive. (2) Large number of statistical tests. (3) Need very, very large samples (10,000 or more.

  8. Results from GWAS (1) Good success in medicine. (2) Limited success for psychiatric disorders (but things are improving) (3) Virtually no success for normal behavioral traits (personality, IQ) (4) Genetics of behavior is hyper-polygenic: many, many, many genes

  9. From The Consortium on Tobacco and Genetics (2010)

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