Simple method to analyze SNP-based association studies using DNA pools
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Updated: Sep 11, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Published on: June 23, 2012
Peter M Visscher1, Stéphanie Le Hellard
1Institute of Cell, Animal, and Population Biology, University of Edinburgh, Edinburgh, United Kingdom. peter.visscher@ed.ac.uk
Abstract:
Association studies using DNA pools are in principle powerful and efficient to detect association between a marker allele and disease status, e.g., in a case-control design. A common observation with the use of DNA pools is that the two alleles at a polymorphic SNP locus are not amplified in equal amounts in heterozygous individuals. In addition, there are pool-specific experimental errors so that there is variation in the estimates of allele frequencies from different pools that are from the same individuals. As a result of these additional sources of variation, the outcome of an experiment is an estimated count of alleles rather than the usual outcome in terms of observed counts. In this study, we show analytically and by computer simulation that unequal amplification should be taken into account when testing for differences in allele frequencies between pools, and suggest a simple modification of the standard chi(2) test to control the type I error rate in the presence of experimental error variation. The impact of experimental errors on the power of association studies is shown.
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