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List of traits analyzed in the study and the predictive performance of the corresponding PRS models.

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https://figshare.com/articles/dataset/List_of_traits_analyzed_in_the_study_and_the_predictive_performance_of_the_corresponding_PRS_models_/19412380
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For the 1,565 traits analyzed in the study, the following information is shown: trait category, the phenotype ID in Global Biobank Engine (GBE ID), trait name, the types of link functions in a generalized linear model (Gaussian for quantitative traits and Binomial for binary traits), the predictive performance of the genotype-only model, covariate-only model, the full model that considers both genotype and covariates, as well as the incremental predictive performance (Delta[Full, covariates-only]), the number of genetic variants included in the PRS model, the statistical significance of the incremental predictive performance in a hold-out test set consists of a subset of white British individuals in the UK Biobank, whether the p-value is significant after multiple-hypothesis correction (p < 2.5 x 10−5), the score ID in polygenic score (PGS) catalog, the experimental factor ontology term ID of the mapped traits in PGS catalog, and the label of the mapped traits in PGS catalog. (XLSX)

针对本研究分析的1565个性状,现将相关信息展示如下:性状类别、全球生物库引擎(Global Biobank Engine,GBE)中的表型ID(GBE ID)、性状名称、广义线性模型(generalized linear model,GLM)所采用的连接函数类型(定量性状使用高斯连接函数,二分类性状使用二项连接函数)、仅基因型模型、仅协变量模型以及同时纳入基因型与协变量的全模型的预测性能、增量预测性能(Δ[全模型, 仅协变量模型])、多基因风险评分(polygenic risk score,PRS)模型中包含的遗传变异数量、基于英国生物库(UK Biobank)中白人英国裔个体子集构建的留出测试集上的增量预测性能的统计学显著性、经多重假设检验校正后p值是否显著(p < 2.5×10⁻⁵)、多基因评分(polygenic score,PGS)目录中的评分ID、PGS目录中映射性状的实验因子本体论(experimental factor ontology,EFO)术语ID,以及PGS目录中映射性状的标签。(XLSX)
创建时间:
2022-03-24
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