SNP Set Association Testing for Survival Outcomes in the Presence of Intrafamilial Correlation.
In this work, we propose a single nucleotide polymorphism (SNP) set association test for censored phenotypes in the presence of a family-based design. The proposed test is valid for both common and rare variants. A proportional hazards Cox model is specified for the marginal distribution of the trait and the familial dependence is modeled via a Gaussian copula. Censored values are treated as partially missing data and a multiple imputation procedure is proposed in order to compute the test statistics. The P-value is then deduced analytically. The finite-sample empirical properties of the proposed method are evaluated and compared to existing competitors by simulations and its use is illustrated using a breast cancer data set from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2.
Département de mathématiques et de statistique, Université Laval, Québec, Canada.
Martin
M
Leclerc
Department of Molecular Medicine, Canada Research Chair in Oncogenetics, Laval University & Genomics Centre, CHU de Québec Research Centre, Québec, Canada.
Jacques
J
Simard
Département de mathématiques et de statistique, Université Laval, Québec, Canada.
Lajmi
L
Lakhal-Chaieb
D019313:BRCA1 Protein / Q000235:genetics; D024682:BRCA2 Protein / Q000235:genetics; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics / Q000401:mortality; D005260:Female; D056726:Genetic Association Studies; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D016016:Proportional Hazards Models
D019313:BRCA1 Protein; D024682:BRCA2 Protein
Gaussian copula; association test; censored trait; family-based design; multiple imputation; proportional hazards Cox model