Detecting disease association with rare variants in case-parents studies.
Major advances in DNA sequencing technology have generated large quantities of sequence data that promote the development of statistical methods for rare variant association analyses. Although many population-based case control methods have been well developed for rare variant analysis, little work focuses on family-based studies. In this paper, we extend the existing methods to test for association of rare variants with case-parents data. We investigated the influence of non-variants and effects of causal variants on max-, multi-marker test, and collapsing method, and proposed an adaptive strategy based on a difference vector. Using simulations we show that the collapsing method is affected profoundly by the number of non-causal variants and different direction effects of causal variants and multi-marker test is most robust to non-causal variants and effects of causal variants. Our selective-difference strategy can improve power especially for collapsing method.
School of Mathematics and Computational Science, Huaihua University, Hunan, China.
Yu-Mei
YM
Li
School of Mathematics and Computational Science, Huaihua University, Hunan, China.
Yang
Y
Xiang
D003198:Computer Simulation; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D006801:Humans; D010290:Parents; D013997:Time Factors