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

Pedigree Analysis01:35

Pedigree Analysis

Overview
Pedigree Analysis01:35

Pedigree Analysis

Overview
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
Coefficient of Correlation01:12

Coefficient of Correlation

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...
Calculating and Interpreting the Linear Correlation Coefficient01:11

Calculating and Interpreting the Linear Correlation Coefficient

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
Genetic Variation01:25

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles, which...

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

Logica: A likelihood framework for cross-ancestry local genetic correlation estimation using summary statistics.

American journal of human genetics·2025
Same author

Proteome-wide association studies for blood lipids and comparison with transcriptome-wide association studies.

HGG advances·2024
Same author

MESuSiE enables scalable and powerful multi-ancestry fine-mapping of causal variants in genome-wide association studies.

Nature genetics·2024
Same author

Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies.

bioRxiv : the preprint server for biology·2023
Same author

Mendelian randomization under the omnigenic architecture.

Briefings in bioinformatics·2021
Same author

Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studies.

PLoS genetics·2021

相关实验视频

Updated: May 12, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

协议:使用Logica估计跨祖先本地遗传相关性.

Boran Gao1, Zheng Li2, Xiang Zhou3

  • 1Department of Statistics, Purdue University, West Lafayette, IN 47907, USA; Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA.

STAR protocols
|December 25, 2025
PubMed
概括

本研究介绍了Logica,这是一种使用全基因组关联研究 (GWAS) 总结统计数据来估计祖先之间的遗传相关性的新方法. 该协议使得共享遗传架构的可扩展推断成为可能.

关键词:
生物信息学是一种生物信息学.计算机科学 计算机科学遗传学 遗传学 遗传学 是一个基因组学就是基因组学.卫生科学 卫生科学

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

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

相关实验视频

Last Updated: May 12, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

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

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

科学领域:

  • 遗传学 是一个遗传学.
  • 生物信息学是一种生物信息学.
  • 人口遗传学 人口遗传学

背景情况:

  • 了解跨不同种群的遗传相关性对于破译共享遗传架构至关重要.
  • 现有的方法可能缺乏可扩展性或需要个人级别的数据.

研究的目的:

  • 提出一个可复制的协议,以估计跨祖先的本地遗传相关性.
  • 通过总结统计数据,实现共享遗传架构的准确和可扩展的推断.

主要方法:

  • 运用逻辑,一个基于概率的框架.
  • 使用来自全基因组关联研究 (GWAS) 的总结统计数据.
  • 包含的祖先特定的链接不平衡 (LD) 信息.

主要成果:

  • 开发了一种用于估计位置水平遗传性的协议.
  • 启用了跨祖先遗传相关性的估计.
  • 概述了可扩展推理所需的输入和分析程序.

结论:

  • 逻辑协议为跨祖先遗传相关性分析提供了一种可复制的方法.
  • 促进共享遗传架构的准确和可扩展的推断.
  • 对于人口遗传学和GWAS研究来说,这是一个有价值的工具.