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

13.5K
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...
13.5K

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

Correlates of Elder Abuse in São Paulo, Brazil: The Roles of Age, Depression, and Religion.

Journal of religion and health·2026
Same author

FOXM1 inhibition primes terminal differentiation of human iPSC-derived hepatocytes.

Cell death discovery·2026
Same author

Career Intentions in Academic Medicine: Factors Influencing Pursuit and Gender Disparities.

Advances in medical education and practice·2026
Same author

Academic medicine career intentions among medical residents: a social cognitive career theory approach.

BMC medical education·2026
Same author

Are there gender differences in academic medical career aspirations related to research, mentoring and discrimination? A national cross-sectional study of French medical residents.

BMJ open·2026
Same author

Association of Complement Genetics with Outcomes in IgA Nephropathy.

Clinical journal of the American Society of Nephrology : CJASN·2026

相关实验视频

Updated: Jul 11, 2025

Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation
08:07

Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation

Published on: September 6, 2017

10.1K

最佳的人口特异性HLA归算与尺寸缩小.

Venceslas Douillard1, Nayane Dos Santos Brito Silva1,2, Sonia Bourguiba-Hachemi1

  • 1Nantes Université, INSERM, Ecole Centrale Nantes, Center for Research in Transplantation and Translational Immunology, Nantes, France.

HLA
|November 11, 2023
PubMed
概括

准确的人类白细胞抗原 (HLA) 归因对于疾病研究至关重要. 基因特异性参考面板可以提高HLA归算的准确性,特别是在代表性不足的人群中.

关键词:
混合种群的混合种群.缩小尺寸的缩小方式在 HLA 归因过程中,HLA 归因.免疫基因组学是什么

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
Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

28.1K

相关实验视频

Last Updated: Jul 11, 2025

Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation
08:07

Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation

Published on: September 6, 2017

10.1K
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
Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

28.1K

科学领域:

  • 人类基因组学 人类基因组学
  • 免疫遗传学 免疫遗传学
  • 人口遗传学 人口遗传学

背景情况:

  • 全基因组关联研究 (GWAS) 是强大的,但仅限于单核酸多态 (SNP) 数据.
  • 基于SNP的GWAS无法捕捉人类白细胞抗原 (HLA) 基因的高多态性,这些基因对疾病易感性至关重要.
  • 目前的HLA归算方法由于参考小组缺乏多样性而陷入困境.

研究的目的:

  • 评估1000个基因组数据的准确性,作为非洲和欧洲祖先混合个体HLA归因的参考面板.
  • 为了比较不同参考面板策略的性能,包括完整的数据集,复制的子集和自定义面板.
  • 突出需要基因特异型模型,在多种人群中准确地归算HLA.

主要方法:

  • 使用1000个基因组数据集对HLA归算准确性的评估.
  • 使用完整数据集,来自6个群体的10个复制子集和19个自定义参考面板条件来测试归算性能.
  • 定制模型与多民族和特定人口模型的比较.

主要成果:

  • 完整的1000个基因组数据集表现良好,HLA-B.的F1得分为0.66,达到0.66的F1得分.
  • 定制制造的参考面板显著优于多民族或类似规模的人口模型 (F1得分高达0.53而不是高达0.42).
  • 基因特异型模型对于提高HLA归算准确性至关重要,特别是对于代表性不足的群体.

结论:

  • 1000个基因组数据集为HLA归算提供了有价值的资源,较大的数据集通常会产生更好的结果.
  • 针对特定人群量身定制的定制参考面板,与更广泛的模型相比,在HLA归算方面提供了更高的准确性.
  • 这项研究强调了开发和利用基因特异性归算模型的重要性,以增强所有人群的HLA基因型定型,推进遗传研究和疾病关联研究.