Adaptive tests for association analysis of rare variants
1Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455–0392, USA. weip@biostat.umn.edu
Abstract:
In anticipation of the availability of next-generation sequencing data, there has been increasing interest in association analysis of rare variants (RVs). Owing to the extremely low frequency of a RV, single variant-based analysis and many existing tests developed for common variants may not be suitable. Hence, it is of interest to develop powerful statistical tests to assess association between complex traits and RVs with sequence data. Recently, a pooled association test based on variable thresholds (VT) was proposed and shown to be more powerful than some existing tests (Price et al. [2010] Am J Hum Genet 86:832-838). In this study, we generalize the VT test of Price et al. in several aspects. We propose a general class of adaptive tests that covers the VT test of Price et al. as a special case. In particular, we show that some of our proposed adaptive tests may substantially improve the power over the pooled association tests, including the VT test of Price et al., especially so in the presence of many neutral RVs and/or of causal RVs with opposite association directions, in which cases most of the existing pooled association tests suffer from significant loss of power. Our proposed tests are also general and flexible with the ability to incorporate weights on RVs and to adjust for covariates.
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