Multivariate Quantitative Multifactor Dimensionality Reduction for Detecting Gene-Gene Interactions.
Hum Hered
; 79(3-4): 168-81, 2015.
Article
em En
| MEDLINE
| ID: mdl-26201702
ABSTRACT
OBJECTIVES:
To determine gene-gene interactions and missing heritability of complex diseases is a challenging topic in genome-wide association studies. The multifactor dimensionality reduction (MDR) method is one of the most commonly used methods for identifying gene-gene interactions with dichotomous phenotypes. For quantitative phenotypes, the generalized MDR or quantitative MDR (QMDR) methods have been proposed. These methods are known as univariate methods because they consider only one phenotype. To date, there are few methods for analyzing multiple phenotypes.METHODS:
To address this problem, we propose a multivariate QMDR method (Multi-QMDR) for multivariate correlated phenotypes. We summarize the multivariate phenotypes into a univariate score by dimensional reduction analysis, and then classify the samples accordingly into high-risk and low-risk groups. We use different ways of summarizing mainly based on the principal components. Multi-QMDR is model-free and easy to implement.RESULTS:
Multi-QMDR is applied to lipid-related traits. The properties of Multi- QMDR were investigated through simulation studies. Empirical studies show that Multi-QMDR outperforms existing univariate and multivariate methods at identifying causal interactions.CONCLUSIONS:
The Multi-QMDR approach improves the performance of QMDR when multiple quantitative phenotypes are available.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Epistasia Genética
/
Redução Dimensional com Múltiplos Fatores
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Hum Hered
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
Coréia do Sul