Genotype-Based Score Test for Association Testing in Families.

Area of Science:

• Genetics
• Statistical Genetics
• Bioinformatics

Background:

• Multiplex-case and control study designs involve multiple cases from the same family.
• Phenotype data from un-genotyped relatives in family studies may be available.
• Integrating family information can enhance genetic association tests.

Purpose of the Study:

• To revisit and enhance a score test for genetic association studies.
• To improve the power of association tests by incorporating available family information.
• To provide a flexible framework for various genetic models and data types.

Main Methods:

• Revisiting a score test to accommodate various genetic models.
• Accounting for correlations in multiplex families and X-linked SNPs.
• Incorporating phenotypic data from un-genotyped relatives using weighted multiplex cases.
• Directly integrating posterior probabilities of imputed genotypes.

Main Results:

• The proposed score test accounts for pedigree-induced correlations and mixed-sex samples.
• It effectively incorporates additional phenotypic data and imputation uncertainty.
• Simulations demonstrate the efficiency and improved power of the proposed test.

Conclusions:

• The revisited score test offers a powerful and flexible approach for genetic association studies using multiplex family data.
• This method enhances the utilization of available family and phenotypic information.
• The approach is robust to genotype imputation uncertainty and applicable to real-world genetic studies.