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全基因组关联研究分析

Analysis of Genome-Wide Association Studies.

作者信息

Gampawar Piyush, Hofer Edith, Alonso Nerea

机构信息

Division of General Paediatrics, Medical University of Graz, Graz, Austria.

Department of Neurology, Medical University of Graz, Graz, Austria.

出版信息

Methods Mol Biol. 2025;2885:695-715. doi: 10.1007/978-1-0716-4306-8_34.

Abstract

Genome-wide association studies (GWAS) aim to identify genetic variants across the whole genome associated with the phenotype of interest. This technique has been largely used in the bone field to elucidate the genetic architecture of complex traits, like bone mineral density or fracture risk, and to date, more than 600 loci have been identified. To ensure that the associations are reliable, a careful design is required, depending upon the phenotype and the sample size, as well as the implementation of adequate quality control measures at both variant and sample levels. There is several software freely available to perform these studies, and different approaches can help increase the number of analyzed genetic variants, like imputation, or the sample size (meta-analysis). Further post-GWAS analysis can be applied to investigate the possible biological function and potential therapeutic relevance of the identified loci.

摘要

全基因组关联研究(GWAS)旨在识别全基因组范围内与感兴趣的表型相关的基因变异。这项技术在骨领域已被广泛应用,以阐明复杂性状(如骨密度或骨折风险)的遗传结构,迄今为止,已鉴定出600多个基因座。为确保关联可靠,需要根据表型、样本量进行精心设计,并在变异和样本层面实施适当的质量控制措施。有几种免费软件可用于进行这些研究,不同的方法可以帮助增加分析的基因变异数量,如填充或样本量(荟萃分析)。进一步的GWAS后分析可用于研究已鉴定基因座的可能生物学功能和潜在治疗相关性。

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