Your browser doesn't support javascript.
loading
A powerful test for ordinal trait genetic association analysis.
Xue, Yuan; Wang, Jinjuan; Ding, Juan; Zhang, Sanguo; Li, Qizhai.
Afiliación
  • Xue Y; School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China.
  • Wang J; Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing, China.
  • Ding J; LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
  • Zhang S; School of Mathematics and Statistics, Guangxi Normal University, Guilin, China.
  • Li Q; School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China.
Stat Appl Genet Mol Biol ; 18(2)2019 01 26.
Article en En | MEDLINE | ID: mdl-30685746
Response selective sampling design is commonly adopted in genetic epidemiologic study because it can substantially reduce time cost and increase power of identifying deleterious genetic variants predispose to human complex disease comparing with prospective design. The proportional odds model (POM) can be used to fit data obtained by this design. Unlike the logistic regression model, the estimated genetic effect based on POM by taking data as being enrolled prospectively is inconsistent. So the power of resulted Wald test is not satisfactory. The modified POM is suitable to fit this type of data, however, the corresponding Wald test is not optimal when the genetic effect is small. Here, we propose a new association test to handle this issue. Simulation studies show that the proposed test can control the type I error rate correctly and is more powerful than two existing methods. Finally, we applied three tests to Anticyclic Citrullinated Protein Antibody data from Genetic Workshop 16.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Simulación por Computador / Pruebas Genéticas / Estudios de Asociación Genética / Modelos Genéticos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Stat Appl Genet Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2019 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Simulación por Computador / Pruebas Genéticas / Estudios de Asociación Genética / Modelos Genéticos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Stat Appl Genet Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2019 Tipo del documento: Article País de afiliación: China