Gene Hunting: Design and statistics
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Transcript of Gene Hunting: Design and statistics
Gene Hunting:Design and statistics
Phenotype:
Genotype:
Schiz:
Not Schiz:
AA AC CC
Do c2 test for association.
Population-based Association Design:Qualitative Phenotype
Population-based Association Design:Quantitative Phenotype
Number of C alleles
0(AA)
1(AC)
2(CC)
Phen
otyp
e
Compute the correlation (or regression slope)
GWAS: Genome-wideAssociation Study
1. DNA arrays with 1,000s of SNPs scattered throughout the genome. (Current chips in 2009 has over 1,000, 000 different SNPs)
2. Select the SNPs so that they cover ALL the genome using haplotype blocks. (Some DNA chips oversample SNPs in protein coding regions)
3. Genotype patients and controls on all the SNPs (or genotype a random sample of the population).
4. Find the SNPs that differ patients from controls (or have a significant correlation with a quantitative phenotype).
5. Problem: number of statistical tests.
From http://www.genome.gov/multimedia/illustrations/GWAS_2012-12.pdf
GWAS results as of 2012
GWAS and Quantitative Phenotype:Height (Weedon et al, 2007)
Note: Effect size = c. 0.2 inches, length of a housefly
Problems with GWAS
(1) Expensive.
(2) Large number of statistical tests.
(3) Need very, very large samples (10,000 or more.
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
From The Consortium on Tobacco and Genetics (2010)