| license: mit | |
| # ContextTAD | |
| ContextTAD is a deep-learning TAD caller that learns boundary evidence from broader local Hi-C windows that capture TAD-scale structural context. Instead of treating boundary prediction as an isolated per-bin classification problem, ContextTAD uses a context-aware representation to produce left- and right-boundary tracks that are explicitly optimized for downstream TAD assembly. | |
| More details, please check our github repo: https://github.com/ai4nucleome/ContextTAD | |