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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.2K
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...
15.2K
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

20.5K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
20.5K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.5K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.5K
Genetic Variation01:25

Genetic Variation

1.2K
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,...
1.2K
Incomplete Dominance01:43

Incomplete Dominance

29.6K
Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
29.6K

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 dish-to-biobank framework links β-cell nutrient-stress programs to genetic and dietary risk for Type 2 Diabetes.

bioRxiv : the preprint server for biology·2026
Same author

A TAD-informed aging-brain xQTL atlas of multi-modal and cell-type-resolved regulatory variation.

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

Stability of oil bodies under pulsed electric field exposure to rapeseed: New insights into improving oil extraction capacity.

Food chemistry·2026
Same author

Single-cell multiomics of neuron activation reveals context-specific genetics of brain disorders.

Science (New York, N.Y.)·2026
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

Gastric metastasis from hormone receptor-positive breast cancer ten years after radical mastectomy: a case report and literature review.

Frontiers in oncology·2026

相关实验视频

Updated: Jan 8, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

11.3K

奇迹:贝叶斯统计方法用于基因水平的罕见变异分析,包含功能注释.

Shengtong Han1, Xiaotong Sun2, Laura Sloofman3

  • 1School of Dentistry, Marquette University, Milwaukee, WI, USA; Department of Human Genetics, University of Chicago, Chicago, IL, USA.

American journal of human genetics
|December 20, 2025
PubMed
概括

我们开发了MIRAGE,这是一种贝叶斯的方法,用于在全外因子测序研究中分析罕见变异. 通过考虑各种变异效应,MIRAGE改进了基因水平关联测试,超过了用于识别自闭症风险基因的现有方法.

关键词:
自闭症自闭症是什么罕见的变种 罕见的变种整体外因子序列的序列.

更多相关视频

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.2K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.5K

相关实验视频

Last Updated: Jan 8, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

11.3K
In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.2K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.5K

科学领域:

  • 人类遗传学 人类遗传学
  • 生物信息学是一种生物信息学.
  • 统计基因组学 统计基因组学

背景情况:

  • 在全外体或基因组测序研究中的罕见变异提供了更大的效果大小,并可以精确确定因果基因.
  • 现有的基于基因的罕见变异关联方法通常依赖于不切实际的假设,导致分析不足.
  • 需要更强大,更灵活的方法来分析遗传研究中的罕见变异.

研究的目的:

  • 提出一种新的贝叶斯方法,MIRAGE (基于混合模型的基因罕见变异分析),用于增强罕见变异关联分析.
  • 通过捕捉基因内变异效应的异质性来解决当前方法的局限性.
  • 提高识别与复杂疾病相关的基因的功率和准确性,使用罕见变异.

主要方法:

  • MIRAGE采用混合模型方法来区分基因内的风险和无风险变异.
  • 它分析了来自三位测序或病例控制研究的总结统计数据.
  • 变体为风险变体的先前概率是使用外部遗传信息建模的.

主要成果:

  • 对自闭症外基因测序数据集的模拟和分析表明MIRAGE的性能优于当前的方法.
  • MIRAGE显著提高了罕见变异关联分析的功率.
  • 通过MIRAGE识别的顶级基因显示,已知或可信的自闭症风险基因具有显著的丰富性.

结论:

  • MIRAGE提供了一个强大而灵活的贝叶斯框架,用于罕见变异的基因水平关联测试.
  • 该方法有效地处理变异效应的异质性,从而改善了与疾病相关的基因的发现.
  • "奇迹"在分析人类遗传研究的罕见变异方面取得了重大进展,特别是在自闭症等复杂疾病中.