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A comparison of association statistics between pooled and individual genotypes

Research output: Contribution to journalJournal articlepeer-review

Published
  • Jo Knight
  • Scott F. Saccone
  • Zhehao Zhang
  • Dennis G. Ballinger
  • John P. Rice
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<mark>Journal publication date</mark>03/2009
<mark>Journal</mark>Human Heredity
Issue number4
Volume67
Number of pages7
Pages (from-to)219-225
Publication StatusPublished
Early online date27/01/09
<mark>Original language</mark>English

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.

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.