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Behavioral Genetics and Its Designs

Behavioral Genetics and Its Designs

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...

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Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

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Robust quantitative trait association tests in the parent-offspring triad design: conditional likelihood-based

J-Y Wang¹, J J Tai

¹Department of Healthcare Administration, Asia University, Taichung, Taiwan.

Annals of Human Genetics

|February 3, 2009

Summary

This study introduces robust association tests for quantitative traits using parent-offspring data. These new methods maintain testing power even when the genetic model is uncertain, improving gene mapping for complex diseases.

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Published on: July 27, 2021

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

Genetics
Biostatistics
Complex Disease Research

Background:

Family-based association studies, like the transmission/disequilibrium test (TDT), are crucial for mapping genes in complex diseases.
While TDT is established for binary traits, robust methods for quantitative traits are less explored.
Population stratification can lead to spurious associations, necessitating robust analytical approaches.

Purpose of the Study:

To develop and evaluate robust candidate-gene association tests for quantitative traits using parent-offspring triad families.
To address the limited attention on robust analysis for quantitative traits in complex diseases.
To demonstrate the feasibility of robust association testing in this context.

Main Methods:

Utilized parent-offspring triad families for association analysis.
Introduced score statistics derived from conditional likelihoods under various genetic models.
Applied existing robust procedures to construct novel association tests for quantitative traits.
Conducted simulations to assess type I error rates and statistical power.

Main Results:

The proposed robust association tests demonstrated robustness against misspecification of the underlying genetic model.
Simulations confirmed the reliability of the empirical type I error rates and powers.
The developed methods are feasible for establishing robust candidate-gene association tests.

Conclusions:

Robust association tests can be effectively established for quantitative traits using parent-offspring data.
These tests offer reliable power even when the genetic model is uncertain.
The findings contribute to more accurate gene mapping for complex diseases with quantitative traits.