全基因组关联研究
生物
遗传关联
特质
疾病
假阳性悖论
计算生物学
数据科学
遗传学
单核苷酸多态性
医学
计算机科学
基因
病理
人工智能
基因型
程序设计语言
作者
Urko M. Marigorta,Juan Antonio Rodríguez,Greg Gibson,Arcadi Navarro
标识
DOI:10.1016/j.tig.2018.03.005
摘要
Since the publication of the Wellcome Trust Case Control Consortium (WTCCC) landmark study a decade ago, genome-wide association studies (GWAS) have led to the discovery of thousands of risk variants involved in disease etiology. This success story has two angles that are often overlooked. First, GWAS findings are highly replicable. This is an unprecedented phenomenon in complex trait genetics, and indeed in many areas of science, which in past decades have been plagued by false positives. At a time of increasing concerns about the lack of reproducibility, we examine the biological and methodological reasons that account for the replicability of GWAS and identify the challenges ahead. In contrast to the exemplary success of disease gene discovery, at present GWAS findings are not useful for predicting phenotypes. We close with an overview of the prospects for individualized prediction of disease risk and its foreseeable impact in clinical practice.
科研通智能强力驱动
Strongly Powered by AbleSci AI