Data: Sequence-based regulatory prediction with AlphaGenome complements TWAS for GWAS gene prioritization beyond eQTL-model coverage

Processed data tables, merged AlphaGenome–TWAS gene-level scores, tissue-specificity intermediates, and supplementary tables (S1–S15) supporting the manuscript: Guo & Chen, "Sequence-based regulatory prediction with AlphaGenome complements TWAS for GWAS gene prioritization beyond eQTL-model coverage." Companion to the analysis code at https://github.com/Thewhey-Brian/alphagenome-twas. Raw upstream public data (GWAS sumstats from IEU OpenGWAS, GTEx individual-level data, FUSION TWAS weights, ChEMBL r33, Open Targets 23.12) are not redistributed here — see GitHub README for re-derivation. v2 additions: per-analysis intermediate tables for Figures 1–3 (persnp_vs_gtex, persnp_vs_joint, tissue_specificity); SuSiE 95% credible sets across the 43 traits; AlphaGenome per-SNP score tables (gene-level LFC outputs from the score_variant API, redistributed as derived data under CC-BY-4.0).本数据集包含经预处理的数据表格、整合后的AlphaGenome–转录组全基因组关联分析（Transcriptome-wide Association Study, TWAS）基因水平得分、组织特异性中间文件，以及支持郭与陈论文《基于序列的调控预测模型AlphaGenome可补充TWAS以拓展表达数量性状位点（expression Quantitative Trait Locus, eQTL）模型覆盖范围外的全基因组关联研究（Genome-Wide Association Study, GWAS）基因优先级鉴定》的补充表格（S1–S15）。本数据集配套分析代码详见：https://github.com/Thewhey-Brian/alphagenome-twas。 本数据集未重新分发上游原始公开数据（含来自IEU开放GWAS数据库的GWAS汇总统计量、基因型-组织表达（Genotype-Tissue Expression, GTEx）个体水平数据、FUSION TWAS权重文件、ChEMBL r33版本、Open Targets 23.12版本）——如需重新获取此类数据，请参阅GitHub仓库的README文档。 版本2新增内容：适配图1至图3的逐分析中间表格（persnp_vs_gtex、persnp_vs_joint、tissue_specificity）；覆盖43个性状的SuSiE（Sum of Single Effects）95%可信集；AlphaGenome单SNP得分表格（由score_variant API生成的基因水平对数折叠变化（log2 fold change, LFC）输出结果，以知识共享署名4.0（CC-BY-4.0）许可作为衍生数据重新分发）