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Related Concept Videos

Gene-Environment Interactions01:20

Gene-Environment Interactions

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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...
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Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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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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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Polygenic Traits01:18

Polygenic Traits

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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Heritability01:06

Heritability

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Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic"...
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Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

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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...
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Related Experiment Video

Updated: Aug 9, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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A scalable hierarchical lasso for gene-environment interactions.

Natalia Zemlianskaia1, W James Gauderman1, Juan Pablo Lewinger1

  • 1Division of Biostatistics, Department of Preventive Medicine, University or Southern California.

Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America
|February 16, 2023
PubMed
Summary

This study introduces a new regularized regression model for identifying gene-environment (G×E) interactions. The model efficiently selects relevant genetic and environmental factors, outperforming existing methods in simulations and real-world data analysis.

Keywords:
hierarchical variable selectionjoint analysisscreening rules

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Area of Science:

  • Genetics
  • Biostatistics
  • Computational Biology

Background:

  • Identifying gene-environment (G×E) interactions is crucial for understanding complex diseases.
  • Existing methods for G×E interaction selection face challenges in scalability and accuracy.

Purpose of the Study:

  • To develop a novel regularized regression model for the selection of G×E interactions.
  • To propose an efficient algorithm and screening rules for accurate predictor selection.

Main Methods:

  • A regularized regression model with a main-effect-before-interaction hierarchical structure.
  • An efficient fitting algorithm and screening rules for discarding irrelevant predictors.
  • Simulation studies and real data application for validation.

Main Results:

  • The proposed model demonstrates superior selection performance compared to existing joint selection methods.
  • The model exhibits enhanced scalability and speed in analyzing large datasets.
  • The 'gesso' R package provides an accessible implementation of the developed method.

Conclusions:

  • The new regularized regression model offers an effective and efficient approach for G×E interaction selection.
  • The method improves upon existing techniques in terms of accuracy, scalability, and speed.
  • The availability of the 'gesso' R package facilitates its application in genetic research.