A comparison of association statistics between pooled and ndividual genotypes

Jo Knight, Scott F. Saccone, Zhehao Zhang, Dennis G. Ballinger, John P. Rice

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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. Results and 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.

Original languageEnglish
Pages (from-to)219-225
Number of pages7
JournalHuman heredity
Issue number4
StatePublished - Mar 2009


  • Association
  • Pooling
  • Power


Dive into the research topics of 'A comparison of association statistics between pooled and ndividual genotypes'. Together they form a unique fingerprint.

Cite this