Supplementary Data for Doctoral Thesis: Deep Learning Approaches for an Integrated Study of DNA Sequence, Epigenome and Chromatin Architecture

Supplementary Data for Doctoral Thesis: Deep Learning Approaches for an Integrated Study of DNA Sequence, Epigenome and Chromatin Architecture Appendix A - lists all datasets used in constructing the chromatin feature compendia for the chromatin feature neural network training sets (deepHaem). Appendix B - lists all CaptureC validation probes. ctcf_screen_k562_with_motifs_results.txt.gz - lists the results of the CTCF site in silico insertion screen listing chr start and end pf the CTCF site, nine metrics (only "sum.abs.diff" used in thesis) quantifying the chromatin interaction changes, intersections with CTCF ChIP-seq peak calls and presence, orientation and strength of the motifs as well as a naive integrated motif score.博士学位论文补充数据：用于DNA序列、表观基因组与染色质架构整合研究的深度学习方法 附录A：列出了构建染色质特征神经网络训练集（deepHaem）所用的全部染色质特征汇编数据集。 附录B：列出了全部CaptureC验证探针。 ctcf_screen_k562_with_motifs_results.txt.gz：记录了CTCF位点计算机模拟插入筛选的结果，涵盖CTCF位点的染色体编号、起始与终止位置、9项用于量化染色质互作变化的指标（本论文仅使用了"sum.abs.diff"一项）、与CTCF ChIP-seq峰调用结果的交集、基序的存在性、方向与强度，以及一种简易整合基序得分。