Gene-trait similarity regression for multimarker-based association analysis

Jung Ying Tzeng, Daowen Zhang, Sheng Mao Chang, Duncan C. Thomas, Marie Davidian

Research output: Contribution to journalArticle

37 Citations (Scopus)

Abstract

We propose a similarity-based regression method to detect associations between traits and multimarker genotypes. The model regresses similarity in traits for pairs of "unrelated" individuals on their haplotype similarities, and detects the significance by a score test for which the limiting distribution is derived. The proposed method allows for covariates, uses phase-independent similarity measures to bypass the needs to impute phase information, and is applicable to traits of general types (e.g., quantitative and qualitative traits). We also show that the gene-trait similarity regression is closely connected with random effects haplotype analysis, although commonly they are considered as separate modeling tools. This connection unites the classic haplotype sharing methods with the variance-component approaches, which enables direct derivation of analytical properties of the sharing statistics even when the similarity regression model becomes analytically challenging.

Original languageEnglish
Pages (from-to)822-832
Number of pages11
JournalBiometrics
Volume65
Issue number3
DOIs
Publication statusPublished - 2009 Sep 1

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All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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