Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data

نویسندگان

  • Jing Huang
  • Yong Chen
  • Michael D Swartz
  • Iuliana Ionita-Laza
چکیده

We apply a family-based extension of the sequence kernel association test (SKAT) to 93 trios extracted from the 20 pedigrees in the Genetic Analysis Workshop 18 simulated data. Each extracted trio includes a unique set of parents to ensure conditionally independent trios are sampled. We compare the empirical type I error and power between the family-based SKAT and the burden test under varying percentages of causal single-nucleotide polymorphisms included in the analysis. Our investigation using simulated data suggests that, under the setting used for Genetic Analysis Workshop 18 data, both the family-based SKAT and the burden test have limited power, and that there is no substantial impact of percentage of signal on the power of either test. The low power is partially a result of the small sample size. However, we find that both the family-based SKAT and the burden test are more powerful when we use only rare variants, rather than common variants, to test the association.

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عنوان ژورنال:

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2014