Abstract
Case-control association studies often suffer from population stratification bias. A previous triple combination strategy of stratum matching, genomic controlling, and multiple DNA pooling can correct the bias and save genotyping cost. However the method requires researchers to prepare a multitude of DNA pools—more than 30 case-control pooling sets in total (polyset). In this paper, the authors propose a permutation test for oligoset DNA pooling studies. Monte-Carlo simulations show that the proposed test has a type I error rate under control and a power comparable to that of individual genotyping. For a researcher on a tight budget, oligoset DNA pooling is a viable option.
Highlights
Case-control association studies often suffer from population stratification bias [1,2,3,4]
Monte Carlo simulations were performed to examine the statistical properties of the permutation test
The permutation test has a type I error rate under control. This means that the all-in-one design by itself is a legitimate method for testing marker-disease association
Summary
Case-control association studies often suffer from population stratification bias [1,2,3,4]. Huang and Lee [5] recently proposed a triple combination strategy, which combines stratum matching, genomic controlling, and multiple DNA pooling. The strategy can correct population stratification bias and save genotyping cost. Huang and Lee’s method [5] is a large-sample method for polyset DNA pooling studies, requiring researchers to prepare a multitude of DNA pools—more than 30 case-control pooling sets in totals. This may be impractical for most DNA pooling studies. We use simulated and real data to demonstrate our method
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