A two-phase procedure for non-normal quantitative trait genetic association study.
BMC Bioinformatics
; 17: 52, 2016 Jan 28.
Article
em En
| MEDLINE
| ID: mdl-26821800
ABSTRACT
BACKGROUND:
The nonparametric trend test (NPT) is well suitable for identifying the genetic variants associated with quantitative traits when the trait values do not satisfy the normal distribution assumption. If the genetic model, defined according to the mode of inheritance, is known, the NPT derived under the given genetic model is optimal. However, in practice, the genetic model is often unknown beforehand. The NPT derived from an uncorrected model might result in loss of power. When the underlying genetic model is unknown, a robust test is preferred to maintain satisfactory power.RESULTS:
We propose a two-phase procedure to handle the uncertainty of the genetic model for non-normal quantitative trait genetic association study. First, a model selection procedure is employed to help choose the genetic model. Then the optimal test derived under the selected model is constructed to test for possible association. To control the type I error rate, we derive the joint distribution of the test statistics developed in the two phases and obtain the proper size.CONCLUSIONS:
The proposed method is more robust than existing methods through the simulation results and application to gene DNAH9 from the Genetic Analysis Workshop 16 for associated with Anti-cyclic citrullinated peptide antibody further demonstrate its performance.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Variação Genética
/
Modelos Estatísticos
/
Dineínas do Axonema
/
Estudos de Associação Genética
/
Modelos Genéticos
Tipo de estudo:
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article