A Comparison of Association Statistics between Pooled and Individual Genotypes

TY - JOUR

T1 - A Comparison of Association Statistics between Pooled and Individual Genotypes

AU - Knight, Jo

AU - Saccone, Scott F.

AU - Zhang, Zhehao

AU - Ballinger, Dennis G.

AU - Rice, John P.

PY - 2009/3

Y1 - 2009/3

N2 - 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. Copyright (C) 2009 S. Karger AG, Basel

AB - 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. Copyright (C) 2009 S. Karger AG, Basel

U2 - 10.1159/000194975

DO - 10.1159/000194975

M3 - Article

VL - 67

SP - 219

EP - 225

JO - Human Heredity

JF - Human Heredity

IS - 4

ER -