Evolutionary Models and Algorithms for Tumor Phylogeny Inference

Explore evolutionary models and computational algorithms for inferring tumor phylogenies in this 20-minute conference talk from the Computational Genomics Summer Institute. Learn about cutting-edge approaches to reconstructing the evolutionary history of tumors using genomic data, with focus on copy-number constrained mutation loss models and single-cell sequencing applications. Discover how computational methods like ConDoR address the challenges of tumor phylogeny inference by incorporating copy-number constraints, and examine related algorithms including SCARLET for single-cell tumor phylogeny inference and SPhyR for handling mutation losses and sequencing errors. Gain insights into the mathematical foundations and practical implementations of tree inference methods specifically designed for cancer genomics, understanding how these tools help researchers trace the evolutionary pathways of tumor development and progression.