Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Polygenic Traits01:18

Polygenic Traits

65.7K
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...
65.7K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

13.3K
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...
13.3K
Multiple Allele Traits01:49

Multiple Allele Traits

34.2K
The Concept of Multiple Allelism
34.2K
Epistasis Analysis01:09

Epistasis Analysis

5.0K
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...
5.0K
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

353
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...
353
Pedigree Analysis01:35

Pedigree Analysis

84.2K
Overview
84.2K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A Multi-Context Regulome-Wide Association Atlas for Genetic Studies of Aging Brain Disorders.

medRxiv : the preprint server for health sciences·2026
Same author

Conserved mechanisms of plant lipidome remodeling under heat and cold stresses revealed through a systematic review and meta-analysis.

Journal of experimental botany·2026
Same author

Remote Language Assessment in School-Age Children With Phelan-McDermid Syndrome and Genotype-Phenotype Correlation.

American journal of medical genetics. Part A·2026
Same author

When does accounting for gene-environment interactions improve complex trait prediction? A case study with Drosophila lifespan.

G3 (Bethesda, Md.)·2025
Same author

The role of genetic variation in shaping phenotypic responses to diet in aging Drosophila melanogaster.

Heredity·2025
Same author

When does accounting for gene-environment interactions improve complex trait prediction? A case study with <i>Drosophila</i> lifespan.

bioRxiv : the preprint server for biology·2025

相关实验视频

Updated: Jun 26, 2025

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.2K

从总结数据中改进多基因预测,通过学习跨多个表型的效应共享模式来改进多基因预测.

Deborah Kunkel1, Peter Sørensen2, Vijay Shankar3

  • 1School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC, United States of America.

bioRxiv : the preprint server for biology
|May 20, 2024
PubMed
概括

我们开发了mr.mash-rss,这是一种新的多基因预测方法,仅使用来自全基因组协会研究 (GWAS) 的总结统计数据. 这种方法提高了复杂特征的遗传预测模型的适用性和可扩展性.

更多相关视频

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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

Published on: June 21, 2018

10.1K

相关实验视频

Last Updated: Jun 26, 2025

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.2K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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

Published on: June 21, 2018

10.1K

科学领域:

  • 人类遗传学 人类遗传学
  • 统计遗传学 统计遗传学
  • 精准医学是一门精准的医学.

背景情况:

  • 复杂特征的多基因预测对于精准医学至关重要.
  • 像Mr.Mash这样的现有方法需要个体级遗传数据,限制了可访问性.
  • 需要使用公开可用的总结统计数据的方法.

研究的目的:

  • 引入mr.mash-rss,这是mr.mash的扩展,仅使用总结统计和链接不平衡 (LD) 数据.
  • 提高多现象型预测模型的适用性和可扩展性.
  • 为了使用随时可用的全基因组协会研究 (GWAS) 总结数据来实现多基因预测.

主要方法:

  • 开发了Mr.Mash-rss,这是一个新的统计模型,扩展了Mr.Mash.
  • 该模型通过使用GWAS总结统计数据共同分析多个表型.
  • 包括参考小组的链接不平衡 (LD) 估计.

主要成果:

  • 在模拟中,mr.mash-rss与最先进的方法相比,表现出具有竞争力和卓越的性能.
  • 在预测来自英国生物库数据的16种血细胞表型方面,超过现有方法,特别是在较小的样本尺寸下.
  • 在各种场景中实现更高的预测准确性,包括不同的效果共享模式和特征号码.

结论:

  • 通过利用总结统计数据,Mr.Mash-rss显著扩大了先进的多基因预测方法的实用性.
  • 该方法可扩展到大型生物库大小的数据集,并适用于非公开的个人级数据.
  • 为人类遗传学和精准医学研究中的遗传预测提供了强大的工具.