New adjustment factors and sample size calculation in a DNA-pooling experiment with preferential amplification

In the post-genome era, disease gene mapping using dense genetic markers has become an important tool for dissecting complex inheritable diseases. Locating disease susceptibility genes using DNA-pooling experiments is a potentially economical alternative to those involving individual genotyping. The foundation of a successful DNA-pooling association test is a precise and accurate estimation of allele frequency. In this article, we propose two new adjustment methods that correct for preferential amplification of nucleotides when estimating the allele frequency of single-nucleotide polymorphisms. We also discuss the effect of sample size when calibrating unequal allelic amplification. We conducted simulation studies to assess the performance of different adjustment procedures and found that our proposed adjustments are more reliable with respect to the estimation bias and root mean square error compared with the current approach. The improved performance not only improves the accuracy and precision of allele frequency estimations but also leads to more powerful disease gene mapping.