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Comparative Study
. 2009;67(4):219-25.
doi: 10.1159/000194975. Epub 2009 Jan 27.

A comparison of association statistics between pooled and individual genotypes

Jo Knight  1 , Scott F Saccone, Zhehao Zhang, Dennis G Ballinger, John P Rice
Affiliations
Comparative Study

A comparison of association statistics between pooled and individual genotypes

Jo Knight et al. Hum Hered. 2009.

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.

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Figures

Fig. 1
Fig. 1
A simulated data set from a mixture of bivariate normal distributions. The squares represent data points from 13% of the data which have a correlation of zero and the crosses represent data points from the other 87% of the data which have a correlation of 0.65. b The association test statistics from the pooled DNA analysis and the individual DNA analysis. x = test statistics derived from pooled DNA; z = test statistics derived from individually typed DNA.
Fig. 2
Fig. 2
The percentage of markers plotted against the number of pools passing QC. All 16 pools passed QC in 74.6% of the markers but this is not shown on the graph so that the pattern from the rest of the results is easier to see. We only have data on those SNPs that have at least two pools passing QC in both the case and control samples.
Fig. 3
Fig. 3
The proportion of markers selected is plotted against minus log 10 of the expected p value of a causative SNP. The different data series represent three different correlations and two different cut-offs. For simplicity the proportion of the SNPs with an uncorrelated bivariate distribution are not included in the figure.
See this image and copyright information in PMC

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