CCP-DP: Cross-cluster context-guided phase dynamic programming for DNA storage sequence reconstruction

Motivation: DNA data storage offers high information density and long-term stability, but accurate sequence reconstruction remains challenging under limited sequencing coverage and strong insertion, deletion, and substitution (IDS) noise. Existing reconstruction methods mainly rely on local evidence within individual read clusters. When sequencing coverage is low or indel-induced phase shifts become pronounced, such local evidence may be insufficient to distinguish closely competing candidate sequences. Results: We present Cross-Cluster Context-Guided Phase Dynamic Programming (CCP-DP), which uses dataset-level cross-cluster information to complement cluster-local evidence and selectively refines ambiguous provisional consensuses. Under the main benchmark settings, CCP-DP achieved exact reconstruction rates of 95.36%-99.98% and outperformed existing methods on multiple datasets. At $5\times$ coverage, CCP-DP improved exact reconstruction by 6.2-17.5 percentage points over the stronger of BBS and CPL across the tested IDS conditions, while maintaining low reconstruction error and computational overhead. Overall, CCP-DP introduces cross-cluster shared information as a complementary source of evidence for DNA sequence reconstruction under challenging conditions. Availability: Source code is available at https://github.com/ZixinZ3899/CCP-DP.