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相关概念视频

Gene-Environment Interactions01:20

Gene-Environment Interactions

1.0K
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...
1.0K
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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Multiple Allele Traits01:49

Multiple Allele Traits

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The Concept of Multiple Allelism
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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...
978
Epistasis Analysis01:09

Epistasis Analysis

5.6K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.6K
Heritability01:06

Heritability

567
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"...
567

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相关实验视频

Updated: Jan 11, 2026

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

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基因与环境相互作用的坚固混合模型协会测试.

Mengyu Zhang1, Jingxian Tang2, Michael R Brown3

  • 1Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston.

medRxiv : the preprint server for health sciences
|November 19, 2025
PubMed
概括
此摘要是机器生成的。

一个新的强大的混合模型关联测试 (RoM) 改进了对相关个体的基因环境相互作用 (GEI) 分析. 这种方法为大规模遗传研究提供了更好的错误控制和高效的计算.

关键词:
胡伯-怀特三明治估计器大规模的大规模.基因与环境的相互作用.线性混合模型线性混合模型强大的关联测试测试.

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

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相关实验视频

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

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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科学领域:

  • 遗传学 是一个遗传学.
  • 生物统计学 生物统计学
  • 人口遗传学 人口遗传学

背景情况:

  • 线性混合模型 (LMM) 是基因与环境相互作用 (GEI) 研究的标准,考虑了人口结构和相关性.
  • 用LMM进行全基因组GEI测试在计算上很苛刻,容易出现膨胀的I型错误和错误指定的环境影响.
  • 现有的可靠方法往往局限于与人无关的样本,这对与人有关联的基于家庭或基于人口的研究构成了挑战.

研究的目的:

  • 开发和评估一项强大的混合模型关联测试 (RoM),用于在相关样本中高效准确的全基因组GEI分析.
  • 为了解决与传统基于LMM的GEI测试相关的计算强度和I型错误膨胀问题.
  • 为涉及相关个人的大规模GEI研究提供可靠的方法.

主要方法:

  • 建议使用Huber-White三明治估计器进行强大的混合模型关联测试 (RoM).
  • 开发了RoM以进行高效的计算,实现了在受界集群大小下的样本大小的线性缩放.
  • 通过模拟将RoM的性能与基于LMM的两步方法和其他方法进行比较.

主要成果:

  • 模拟表明,与两步方法和替代方法相比,RoM在全基因组显著水平上提供了优越的I型错误控制.
  • 当应用到现实世界的GEI分析时,RoM表现出强大的错误控制和可比的信号检测.
  • 将RoM应用于大型数据集,包括弗雷明汉心脏研究,ARIC和英国生物银行,用于对人类特征和性别的GEI分析.

结论:

  • RoM是一种高效,强大的方法,用于在相关样本中进行大规模基因环境相互作用分析.
  • 提出的方法有效地控制了I型错误率,优于现有策略.
  • 对于涉及复杂家族结构或人口分层的遗传关联研究,RoM提供了可靠的替代方案.