A powerful and robust test in genetic association studies

Kuang Fu Cheng, Jen Yu Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


There are several well-known single SNP tests presented in the literature for detecting gene-disease association signals. Having in place an efficient and robust testing process across all genetic models would allow a more comprehensive approach to analysis. Although some studies have shown that it is possible to construct such a test when the variants are common and the genetic model satisfies certain conditions, the model conditions are too restrictive and in general difficult to verify. In this paper, we propose a powerful and robust test without assuming any model restrictions. Our test is based on the selected 2 × 2 tables derived from the usual 2 × 3 table. By signals from these tables, we show through simulations across a wide range of allele frequencies and genetic models that this approach may produce a test which is almost uniformly most powerful in the analysis of low- and high-frequency variants. Two cancer studies are used to demonstrate applications of the proposed test.

Original languageEnglish
Pages (from-to)38-46
Number of pages9
JournalHuman Heredity
Issue number1
Publication statusPublished - Jul 2014


  • Association test
  • Genetic model
  • Power
  • Robustness
  • SNP

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics


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