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Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

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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Updated: Jul 4, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

条件转录全基因组关联研究精细映射候选因果基因.

Lu Liu^1,2, Ran Yan^1,2, Ping Guo^1,2

¹Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.

Nature genetics

|January 26, 2024

概括

此摘要是机器生成的。

我们开发了GIFT,这是一种通过条件TWAS进行基因基于整合精细映射的新方法. 通过控制基因表达,GIFT有效地识别了与复杂特征相关的基因,改进了现有的TWAS精细映射方法.

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

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

Published on: July 27, 2021

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

相关实验视频

Last Updated: Jul 4, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

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

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

Published on: July 27, 2021

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

科学领域:

遗传学遗传学是一个
生物信息学是一种生物信息学.
统计遗传学统计遗传学

背景情况:

全转录组关联研究 (TWAS) 将全基因组关联研究 (GWAS) 与表达数据相结合,以识别与复杂特征相关的基因.
现有的TWAS方法在关联区域内精确地绘制因果基因方面面临挑战.

研究的目的:

开发和验证GIFT (基于基因的综合精细映射通过条件TWAS),一种用于精细映射假定因果基因的新方法.
在复杂的特征关联研究中提高基因识别的准确性和分辨率.

主要方法:

GIFT执行条件TWAS分析,明确控制局部地区所有其他基因的基因预测表达 (GReX).
该方法采用频率主义方法,模拟多个基因之间的表达相关性和链接不平衡,并使用概率框架来处理表达预测的不确定性.
GIFT生成校准的P值,以实现强大的精细映射.

主要成果:

与现有方法相比,将GIFT应用于英国六个生物库特征,显示了精细映射分辨率的显著改善,将假定因果基因的设置大小缩小了32.16%至91.32%.
GIFT确定了关键基因,涉及血管调节的血压和脂质代谢在调节脂质水平.

结论:

GIFT是一种有效且统计严格的方法,用于在TWAS中精细地图化因果基因.
鉴定出来的基因提供了对血压和脂质水平等复杂特征背后的生物机制的新见解.