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

What is Population Genetics?01:25

What is Population Genetics?

57.1K
A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
57.1K
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

71.3K
Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
71.3K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.6K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.6K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.2K
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...
12.2K
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

300
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...
300
Heritability01:06

Heritability

180
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"...
180

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

MetaSTAARlite: an all-in-one tool for biobank-scale whole-genome sequencing meta-analysis.

Nature computational science·2026
Same author

Multi-ancestry transcriptome-wide association studies uncover insights into breast cancer genetics and biology.

Nature communications·2026
Same author

A high-penetrance intergenic variant at 9p21 confers melanoma susceptibility.

Research square·2026
Same author

Integrating common and rare variants improves polygenic risk prediction across diverse populations.

Nature communications·2026
Same author

Red Blood Cell Exchange Transfusion for Severe Babesiosis.

JAMA internal medicine·2026
Same author

Male invasive breast carcinoma containing both mucinous and micropapillary components with axillary lymph node metastasis: a rare case report with literature review.

Gland surgery·2026

相关实验视频

Updated: Apr 14, 2026

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

10.8K

评估多祖先全基因组关联方法:统计能力,人口结构和实际影响.

Julie-Alexia Dias1, Tony Chen1, Hua Xing2,3

  • 1Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

medRxiv : the preprint server for health sciences
|March 31, 2025
PubMed
概括

与元分析相比,聚合分析为多祖先全基因组关联研究 (GWAS) 提供了优越的统计能力. 这种方法有效地控制了人口结构,增强了跨多种人群的遗传发现.

关键词:
我们所有人,我们所有人全基因组关联研究研究.进行元分析分析.人口分层的人口分层.英国生物银行

更多相关视频

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

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

Published on: July 27, 2021

5.0K
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.9K

相关实验视频

Last Updated: Apr 14, 2026

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

10.8K
Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

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

Published on: July 27, 2021

5.0K
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.9K

科学领域:

  • 人口遗传学 人口遗传学
  • 基因组流行病学 基因组流行病学
  • 统计遗传学 统计遗传学

背景情况:

  • 多祖先全基因组关联研究 (GWAS) 对于识别不同种群中的遗传变异至关重要.
  • 由于统计能力和人口结构控制方面的挑战,对多祖先GWAS的最佳方法进行了辩论.

研究的目的:

  • 为了比较聚合分析的统计能力和人口结构调整能力与多祖先GWAS的元分析.
  • 提供一个理论框架来解释与不同种群的等位基因频率相关的功率差异.

主要方法:

  • 进行了各种样本大小和祖先组成的大规模模拟.
  • 在英国生物银行和我们所有人研究计划的八个连续和五个二进制特征上进行了真实数据分析.
  • 对比了聚合分析 (单个数据集与主要组件调整) 和元分析 (祖先特定的GWAS跟随总结统计组合).

主要成果:

  • 与元分析相比,聚合分析通常表现出优越的统计能力.
  • 聚合分析有效地调整了跨不同祖先群体的人口分层.
  • 开发了一个理论框架,将功率差异与特定种群的等位基因频率变化联系起来.

结论:

  • 聚合分析是多祖先GWAS的一种强大而可扩展的策略,增强了遗传发现.
  • 这种方法保持了对人口结构的严格控制,在多样化的队列中表现优于传统的元分析.
  • 这些发现在两个大型生物库中得到了验证,为未来的遗传研究提供了聚合分析的支持.