The ‘discovery’ stage of genome-wide association studies required amassing large, homogeneous cohorts. In order to attain clinically useful insights, we must now consider the presentation of disease within our clinics and, by extension, within our medical records. Large-scale use of electronic health record (EHR) data can help to understand phenotypes in a scalable manner, incorporating lifelong and whole-phenome context.

中文翻译：

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编码变量的隐式偏差：解决 EHR-GWAS 数据中的结构化偏差的框架。


全基因组关联研究的“发现”阶段需要积累大量、同质的队列。为了获得临床上有用的见解，我们现在必须考虑诊所内疾病的表现，进而考虑医疗记录中的疾病表现。大规模使用电子健康记录 (EHR) 数据有助于以可扩展的方式了解表型，结合终生和整个表组背景。