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Color Data v2: a user-friendly, open-access database with hereditary cancer and hereditary cardiovascular conditions datasets
Database: The Journal of Biological Databases and Curation ( IF 3.4 ) Pub Date : 2020-11-11 , DOI: 10.1093/database/baaa083
Mark J Berger 1 , Hannah E Williams 1 , Ryan Barrett 1 , Anjali D Zimmer 1 , Wendy McKennon 1 , Huy Hong 1 , Jeremy Ginsberg 1 , Alicia Y Zhou 1 , Cynthia L Neben 1
Affiliation  

Publicly available genetic databases promote data sharing and fuel scientific discoveries for the prevention, treatment and management of disease. In 2018, we built Color Data, a user-friendly, open access database containing genotypic and self-reported phenotypic information from 50 000 individuals who were sequenced for 30 genes associated with hereditary cancer. In a continued effort to promote access to these types of data, we launched Color Data v2, an updated version of the Color Data database. This new release includes additional clinical genetic testing results from more than 18 000 individuals who were sequenced for 30 genes associated with hereditary cardiovascular conditions as well as polygenic risk scores for breast cancer, coronary artery disease and atrial fibrillation. In addition, we used self-reported phenotypic information to implement the following four clinical risk models: Gail Model for 5-year risk of breast cancer, Claus Model for lifetime risk of breast cancer, simple office-based Framingham Coronary Heart Disease Risk Score for 10-year risk of coronary heart disease and CHARGE-AF simple score for 5-year risk of atrial fibrillation. These new features and capabilities are highlighted through two sample queries in the database. We hope that the broad dissemination of these data will help researchers continue to explore genotype–phenotype correlations and identify novel variants for functional analysis, enabling scientific discoveries in the field of population genomics.

中文翻译:

Color Data v2:具有遗传性癌症和遗传性心血管疾病数据集的用户友好型开放访问数据库

公开可用的遗传数据库促进数据共享并推动疾病预防、治疗和管理的科学发现。2018 年,我们建立了 Color Data,这是一个用户友好的开放访问数据库,其中包含来自 50 000 个人的基因型和自我报告的表型信息,这些人对 30 个与遗传性癌症相关的基因进行了测序。为了继续努力促进对这些类型数据的访问,我们推出了 Color Data v2,这是 Color Data 数据库的更新版本。这一新版本包括来自 18000 多名个体的额外临床基因检测结果,这些个体对与遗传性心血管疾病相关的 30 个基因以及乳腺癌、冠状动脉疾病和心房颤动的多基因风险评分进行了测序。此外,我们使用自我报告的表型信息来实施以下四种临床风险模型:5 年乳腺癌风险的 Gail 模型、终生乳腺癌风险的 Claus 模型、基于办公室的简单 Framingham 冠心病风险评分 10 年冠心病风险和 CHARGE-AF 心房颤动 5 年风险简单评分。这些新特性和功能通过数据库中的两个示例查询突出显示。我们希望这些数据的广泛传播将有助于研究人员继续探索基因型 - 表型相关性并识别用于功能分析的新变体,从而实现群体基因组学领域的科学发现。简单的基于办公室的弗雷明汉冠心病风险评分,用于 10 年冠心病风险和 CHARGE-AF 简单评分,用于 5 年心房颤动风险。这些新特性和功能通过数据库中的两个示例查询突出显示。我们希望这些数据的广泛传播将有助于研究人员继续探索基因型 - 表型相关性并识别用于功能分析的新变体,从而实现群体基因组学领域的科学发现。简单的基于办公室的弗雷明汉冠心病风险评分,用于 10 年冠心病风险和 CHARGE-AF 简单评分,用于 5 年心房颤动风险。这些新特性和功能通过数据库中的两个示例查询突出显示。我们希望这些数据的广泛传播将有助于研究人员继续探索基因型 - 表型相关性并识别用于功能分析的新变体,从而实现群体基因组学领域的科学发现。
更新日期:2020-11-19
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