Adaptive robust genetic association tests using case-parents triad families

Area of Science:

• Genetics
• Biostatistics
• Statistical Genetics

Background:

• Model-specific score tests are powerful for genetic association studies with case-parent trios but lose power if the genetic model is misspecified.
• Existing robust tests offer some protection against model misspecification but can be computationally intensive or lack sufficient power robustness.

Purpose of the Study:

• To develop novel, data-driven adaptive robust genetic association tests for case-parent triad data.
• To address limitations of existing methods by improving computational efficiency and power robustness against model misspecification.

Main Methods:

• Proposed two adaptive robust tests: WMERT (Weighted Maximizing Efficiency Robust Test) and WMAX (Weighted Maximum Test Statistic).
• Utilized a data-driven procedure for constructing these tests.
• Evaluated performance using simulations and a real dataset of neural tube defect families.

Main Results:

• WMERT demonstrated computational simplicity and good power robustness.
• WMAX exhibited stable empirical power, comparable to model-specific tests.
• Both proposed tests showed benefits for practical genetic association studies.

Conclusions:

• The proposed WMERT and WMAX tests provide effective and robust alternatives for genetic association analysis in family studies.
• These methods are particularly valuable when the underlying genetic model is uncertain or misspecified.
• Provided R-scripts facilitate the practical application of these novel statistical approaches.