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Related Concept Videos

Gene-Environment Interactions01:20

Gene-Environment Interactions

Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
Behavioral Genetics and Its Designs01:23

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...
Complementation Tests00:49

Complementation Tests

A complementation test is a simple cross to identify whether the two mutations are located on the same gene or different genes. It was first performed by Edward Lewis in the 1940s while working on fruit flies. He developed the test to identify the location and arrangement of different mutations on chromosomes.
Organisms heterozygous for different mutations are crossed pairwise in all combinations. If present on different genes, the mutations can complement each other by providing the missing...
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Related Experiment Video

Updated: Jun 13, 2026

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
08:09

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

Published on: January 7, 2014

Permutation and parametric bootstrap tests for gene-gene and gene-environment interactions.

Petra Bůžková1, Thomas Lumley, Kenneth Rice

  • 1Department of Biostatistics, University of Washington, Seattle, USA. buzkova@u.washington.edu

Annals of Human Genetics
|April 14, 2010
PubMed
Summary

Permutation tests are often unreliable for genetic association studies. A parametric bootstrap approach is a better alternative for testing gene-gene and gene-environment interactions.

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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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Published on: November 3, 2010

Area of Science:

  • Genomics
  • Statistical genetics
  • Bioinformatics

Background:

  • Permutation tests are common in genomic research for statistical inference without strict distributional assumptions.
  • However, their applicability to gene-gene or gene-environment interaction hypotheses in genetic association studies is limited.

Purpose of the Study:

  • To investigate the limitations of permutation tests for interaction hypotheses in genetic association studies.
  • To introduce and evaluate a parametric bootstrap approach as an alternative.

Main Methods:

  • The study compares the finite-sample properties of permutation tests and a parametric bootstrap approach using simulations.
  • Interactions involving single and multiple polymorphisms with an exposure were analyzed.

Main Results:

  • Exact permutation tests are often not feasible for interaction hypotheses in genetic association studies.
  • The parametric bootstrap approach is presented as a viable alternative.
  • Conditions under which permutation tests may be approximately valid in large samples are discussed.

Conclusions:

  • Permutation tests have limitations for testing interactions in genetic association studies.
  • A parametric bootstrap method offers a more reliable approach for interaction analysis.
  • Further research is needed to define the precise conditions for approximate validity of permutation tests in large samples.