Additional file 2 of MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors

Additional file 2: Table S1. H3K27ac active cancer consensus genes in 3 NBL cell lines, and 3 NBL O–PDX samples. Table S2. Baseline models vs. vanilla M2A predictive performance comparison. Table S3. M2A predictive performance in NBL cell line samples. Table S4. Observed H3K27ac and H3K4me3 ENCODE replicate consistencies. Table S5. M2A predictive performance in RMS O–PDX samples. Table S6. M2A RMS transfer model predictive performance in RMS O–PDX samples. Table S7. M2A predictive performance in ENCODE dataset. Table S8. M2A predictive performance in AML samples. Table S9. ERMS vs. ARMS DMRs and associated genes (overexpressed in ERMS). Table S10. ERMS vs. ARMS DMRs and associated genes (overexpressed in ARMS). Table S11. M2A alternate promoter usage predictive performance between ARMS and ERMS samples. Table S12. M2A predictive performance in EWS samples, before and after transfer. Table S13. A univariate survival analysis of differential H3K27ac promoter activity between TP53 mutant and TP53 wild–type EWS tumors. Table S14. A univariate survival analysis of alternate promoter usage between TP53 mutant and TP53 wild–type EWS tumors. Table S15. ENCODE H3K27ac replicate consistency with gene expression. Table S16. Dataset availability. Table S17. M2A model topologies. Table S18. Parameter tuning: mean performance in the NBL validation set (R2). Table S19. Sample summary information.附加文件2：表S1 3株神经母细胞瘤 (Neuroblastoma, NBL) 细胞系及3株NBL O–PDX样本中的H3K27ac活性癌症共识基因。 表S2 基准模型与标准M2A模型的预测性能对比。 表S3 M2A模型在NBL细胞系样本中的预测性能。 表S4 观测到的H3K27ac与H3K4me3的ENCODE (DNA元件百科全书, Encyclopedia of DNA Elements) 重复一致性。 表S5 M2A模型在横纹肌肉瘤 (Rhabdomyosarcoma, RMS) O–PDX样本中的预测性能。 表S6 基于RMS O–PDX样本的M2A RMS迁移模型预测性能。 表S7 M2A模型在ENCODE数据集上的预测性能。 表S8 M2A模型在急性髓系白血病 (Acute Myeloid Leukemia, AML) 样本中的预测性能。 表S9 胚胎型横纹肌肉瘤 (Embryonal Rhabdomyosarcoma, ERMS) 与腺泡型横纹肌肉瘤 (Alveolar Rhabdomyosarcoma, ARMS) 的差异甲基化区域 (Differentially Methylated Regions, DMRs) 及相关基因（ERMS高表达）。 表S10 ERMS与ARMS的差异甲基化区域 (DMRs) 及相关基因（ARMS高表达）。 表S11 M2A模型在ARMS与ERMS样本中的可变启动子使用预测性能。 表S12 迁移学习前后M2A模型在尤文肉瘤 (Ewing Sarcoma, EWS) 样本中的预测性能。 表S13 TP53突变型与TP53野生型EWS肿瘤间差异H3K27ac启动子活性的单变量生存分析。 表S14 TP53突变型与TP53野生型EWS肿瘤间可变启动子使用情况的单变量生存分析。 表S15 ENCODE H3K27ac重复一致性与基因表达的关联。 表S16 数据集可用性说明。 表S17 M2A模型的拓扑结构。 表S18 参数调优：NBL验证集上的平均性能（决定系数R²）。 表S19 样本汇总信息。