当前位置: X-MOL 学术Cell Metab. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Systematically Sifting Big Data to Identify Novel Causal Genes for Human Traits
Cell Metabolism ( IF 27.7 ) Pub Date : 2020-04-07 , DOI: 10.1016/j.cmet.2020.03.013
Nicholas J. Hand , Daniel J. Rader

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.



中文翻译:

系统地筛选大数据以识别人类特质的新型因果基因

广泛的技术进步将人类遗传学推向了“大数据”时代,在这个时代中,来自超大型队列的全基因组数据可以与人类和模型系统的其他“-组学”数据集整合。Li等。(2020年)证明了将多种计算分析应用于公开数据的能力,可以优先研究具有新性状关联的基因。

更新日期:2020-04-20
down
wechat
bug