Vincent (2022-09-30 14:56):
#paper doi: https://doi.org/10.1038/s43586-021-00056-9 Genome-wide association studies. Nature Reviews Methods Primers. 2021. GWAS旨在寻找基因型和表型之间的关联。截止目前,总共有超过5700项,涵盖3300性状的GWAS研究。这篇review文章丛统计原理、实验设计、实际操作、结果解释,下游应用等方面很好地介绍了全基因组关联研究(GWAS)。在统计原理方面,文章介绍了假设检验常用的线性混合模型,假发现率的控制(FDR control)和下游fine mapping方法。实验设计方面,文章详细介绍了人群的选择(population-based, family-based 和 isolation populations),以及测序技术(microarray, WES, WGS)方面的优缺点。应用上,文章介绍了GWAS的两大重要应用:疾病风险预测(PRS score) 和 揭示生物性状的遗传基础。文章最后还提及了GWAS研究目前的局限和对未来发展的期待。总结起来是篇很不错的GWAS入门文章。
Genome-wide association studies
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Abstract:
Genome-wide association studies (GWAS) test hundreds of thousands of genetic variants across many genomes to find those statistically associated with a specific trait or disease. This methodology has generated a myriad of robust associations for a range of traits and diseases, and the number of associated variants is expected to grow steadily as GWAS sample sizes increase. GWAS results have a range of applications, such as gaining insight into a phenotype’s underlying biology, estimating its heritability, calculating genetic correlations, making clinical risk predictions, informing drug development programmes and inferring potential causal relationships between risk factors and health outcomes. In this Primer, we provide the reader with an introduction to GWAS, explaining their statistical basis and how they are conducted, describe state-of-the art approaches and discuss limitations and challenges, concluding with an overview of the current and future applications for GWAS results.
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