Systematically Sifting Big Data to Identify Novel Causal Genes for Human Traits.
Systematically Sifting Big Data to Identify Novel Causal Genes for Human Traits.
复制标题
系统地筛选大数据以识别人类特征的新因果基因。
DOI：
10.1016/j.cmet.2020.03.013
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发表时间：
2020
期刊：
影响因子：
29
通讯作者：
Rader,DanielJ
中科院分区：
文献类型：
--
作者：
Hand,NicholasJ;Rader,DanielJ
广泛的技术进步推动人类遗传学进入了“大数据”时代，在这个时代，来自超大群体的全基因组数据可以与来自人类和模型系统的其他“组学”数据集相结合。Li等人（2020）展示了将多种计算分析应用于公开数据的能力，以优先考虑具有新性状关联的基因的研究。
Widespread technological advances have propelled human genetics into a "big data" era, in which genome-wide data from extremely large cohorts can be integrated with other "-omics" datasets from humans and model systems. Li et al. (2020) demonstrate the power of applying multiple computational analyses to publicly available data to prioritize the study of genes with novel trait associations.