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相关概念视频

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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...
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相关实验视频

Updated: Jul 4, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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转录组广泛的关联研究 (TWAS):方法,应用和挑战

Patrick Evans1, Taylor Nagai1, Anuar Konkashbaev1

  • 1Division of Genetic Medicine and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee.

Current protocols
|February 5, 2024
PubMed
概括
此摘要是机器生成的。

全转录组关联研究 (TWAS) 使用遗传数据将基因表达与特征联系起来. 这种方法有助于识别影响疾病的基因,以便进一步研究.

关键词:
预测可以预测.复杂的特征是复杂的特征.电子健康记录是电子健康记录.关节组织归算 (JTI)单细胞转录组学 单细胞转录组学转录组范围的关联研究 (TWAS)

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相关实验视频

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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.
  • 基因组学就是基因组学.

背景情况:

  • 全转录组关联研究 (TWAS) 通过检查基因表达来弥合遗传变异和表型特征之间的差距.
  • 了解基因特征关联对于剖析复杂疾病和指导功能基因组学研究至关重要.

研究的目的:

  • 提供对全转录组关联研究 (TWAS) 方法的全面概述.
  • 讨论各种TWAS方法的优点,局限性和应用.
  • 突出TWAS在全基因组关联研究 (GWAS) 后分析中的实用性.

主要方法:

  • 基于遗传变异,TWAS使用in silico模型来预测基因表达.
  • 然后将这些预测模型应用于全基因组关联研究 (GWAS) 数据.
  • 这种方法有助于识别具有高可解释性的基因特征关联.

主要成果:

  • 通过TWAS,可以识别调解遗传变异和观察到的表型之间的关系的基因.
  • 该方法提供可解释的基因特征关联,促进下游功能研究.
  • TWAS支持开发生物研究的基因定资源.

结论:

  • TWAS是一种强大的GWAS后分析框架,用于识别受遗传影响的特征.
  • 该方法提高了遗传关联发现的解释性,并支持功能性基因组学.
  • TWAS的方法是促进我们对人类健康和疾病遗传贡献的理解的宝贵工具.