Clonucopya: An end-to-end workflow bridging tumor clonal architecture and drug prioritization

Abstract

Motivation: Intra-tumor heterogeneity limits the effectiveness of anticancer treatments, as distinct clonal populations may respond differently to therapy. Although subclonal inference from sequencing data is well established, translating clonal architecture into actionable drug recommendations remains a major bottleneck. Results: We present Clonucopya, an end-to-end Snakemake workflow that integrates subclonal inference (PyClone-VI, PhyClone) with drug prioritization (PanDrugs2) to link tumor clonal architecture directly to candidate drugs. From genome sequencing data, Clonucopya reconstructs tumor phylogenies, quantifies clone-level prevalence across samples, and ranks FDA/EMA-approved and experimental therapeutic candidates against the somatic mutations detected in each clone. Outputs include clonality plots, per-clone variant and drug tables, and a summary ranking drugs by clonal coverage to highlight broadly active therapeutic candidates. We assess Clonucopya's utility through a real-world longitudinal, multi-region use case, revealing clinically actionable clonal dynamics across tumor progression.