Precision medicine promises to revolutionize treatment, shifting therapeutic approaches from the classical one-size-fits-all to those more tailored to the patient’s individual genomic profile, lifestyle and environmental exposures. Yet, to advance precision medicine’s main objective—ensuring the optimum diagnosis, treatment and prognosis for each individual—investigators need access to large-scale clinical and genomic data repositories. Despite the vast proliferation of these datasets, locating and obtaining access to many remains a challenge. We sought to provide an overview of available patient-level datasets that contain both genotypic data, obtained by next-generation sequencing, and phenotypic data—and to create a dynamic, online catalog for consultation, contribution and revision by the research community. Datasets included in this review conform to six specific inclusion parameters that are: (i) contain data from more than 500 human subjects; (ii) contain both genotypic and phenotypic data from the same subjects; (iii) include whole genome sequencing or whole exome sequencing data; (iv) include at least 100 recorded phenotypic variables per subject; (v) accessible through a website or collaboration with investigators and (vi) make access information available in English. Using these criteria, we identified 30 datasets, reviewed them and provided results in the release version of a catalog, which is publicly available through a dynamic Web application and on GitHub. Users can review as well as contribute new datasets for inclusion (Web: https://avillachlab.shinyapps.io/genophenocatalog/; GitHub: https://github.com/hms-dbmi/GenoPheno-CatalogShiny).

中文翻译：

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GenoPheno：对人类数据集中的大规模表型和下一代测序数据进行编目。

精准医学有望彻底改变治疗方式，将治疗方法从经典的一刀切转变为更适合患者个体基因组特征、生活方式和环境暴露的治疗方法。然而，为了推进精准医学的主要目标——确保每个人的最佳诊断、治疗和预后——研究人员需要访问大规模的临床和基因组数据存储库。尽管这些数据集大量扩散，但定位和访问许多数据集仍然是一个挑战。我们试图提供包含通过下一代测序获得的基因型数据和表型数据的可用患者级数据集的概述，并创建一个动态的在线目录，供研究界咨询、贡献和修订。本综述中包含的数据集符合六个特定的包含参数：(i) 包含来自 500 多个人类受试者的数据；(ii) 包含来自同一受试者的基因型和表型数据；(iii) 包括全基因组测序或全外显子组测序数据；(iv) 每个受试者至少包括 100 个记录的表型变量；(v) 通过网站或与调查人员合作访问，以及 (vi) 以英语提供访问信息。使用这些标准，我们确定了 30 个数据集，对其进行了审查，并在目录的发布版本中提供了结果，该目录可通过动态 Web 应用程序和在 GitHub 上公开获取。用户可以查看并贡献新的数据集以供包含（Web：https://avillachlab.shinyapps.io/genophenocatalog/；GitHub：https://github.com/hms-dbmi/GenoPheno-CatalogShiny）。