title: A comparison of association statistics between pooled and individual genotypes.
abstract: BACKGROUND
  Markers for individual genotyping can be selected using quantitative genotyping of pooled DNA. This strategy saves time and money.
  
  
  METHODS
  To determine the efficacy of this approach, we investigated the bivariate distribution of association test statistics from pooled and individual genotypes. We used a sample of approximately 1,000 samples with individual and pooled genotyping on 40,000 SNPs.
  
  
  CONCLUSIONS
  We found that the distribution of the joint test statistics can be modelled as a mixture of two bivariate normal distributions. One distribution has a correlation of zero, and is probably due to SNPs whose pooled genotyping was unsuccessful. The other distribution has a correlation of approximately 0.65 in our data. This latter distribution is probably accounted for by SNPs whose pooled genotyping accurately predicts the underlying allele frequency. Approximately 87% of the data belongs to this distribution. We also derived a method to investigate the effect of both the correlation and selection cut-off on the relative power of pooling studies. We demonstrate that pooled genotyping has good power to detect SNPs that are truly associated with disease-causing variants for SNPs showing good correlation between pooled and individual genotyping. Therefore, this approach is a cost effective tool for association studies.
authors.affiliation: Social Genetic & Developmental Psychiatry MRC Centre, Institute of Psychiatry, Kings College London, London, UK. j.knight@iop.kcl.ac.uk
authors.forename: Jo
authors.initials: J
authors.lastname: Knight
authors.forename: Scott F
authors.initials: SF
authors.lastname: Saccone
authors.forename: Zhehao
authors.initials: Z
authors.lastname: Zhang
authors.forename: Dennis G
authors.initials: DG
authors.lastname: Ballinger
authors.forename: John P
authors.initials: JP
authors.lastname: Rice
mesh_terms: D019295:Computational Biology / Q000379:methods; D005787:Gene Frequency; D015894:Genome, Human; D005838:Genotype; D006801:Humans; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide / Q000235:genetics