j-paszek/ctbf: Biopsy-Aware Phylogenetic Reconstruction of Cancer Evolution Using Single-Cell Copy Number Profiles

Reconstructing tumour evolution from single-cell copy-number profiles (CNPs) collected across multiple biopsy time points requires methods that explicitly exploit the temporal ordering of biopsies. We introduce a biopsy-aware framework for simulating, reconstructing, and benchmarking copy-number phylogenies under realistic models of genome evolution. The framework treats biopsies as explicit temporal constraints and supports two complementary inference strategies. The first, biopsy-guided ancestry inference, enforces time-consistent parent–child relations and resolves the earliest branching structure using an auxiliary NJ-like step. The second, pairwise NJ-anticentral inference, iteratively selects cell pairs and designates an ancestor by combining anticentrality, plausibility, and parsimony criteria, yielding fully labelled CNP-trees. We evaluate reconstruction accuracy using ancestor–descendant recovery (AD-F1) and Generalized Robinson–Foulds (GRF) distances. Our framework enables not only the reconstruction of copy-number phylogenies but also a controlled assessment of their reliability. By simulating full evolutionary histories, we can compare inferred and true distances, quantify how tumour heterogeneity, biopsy sparsity, and multi-locus events degrade signal, and delineate the limits these factors impose on any method. Within this framework we introduced new NJ-like strategies and demonstrated, across diverse regimes, that principled use of biopsy structure together with informed pairwise ancestry decisions yields substantial improvements in reconstruction accuracy. Upgrades from version 1.0.0: added pairwise-based reconstruction algorithms that infer full CNP trees added framework to evaluate reconstruction algorithms added AD-F1 score computation