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Ken Chen, Ph.D.
Department of Bioinformatics and Computational Biology,
Division of Basic Sciences
The University of Texas MD Anderson Cancer Center
Modeling single-cell copy number evolution reveals novel insight of oncogenesis
Single-cell sequencing provided an unprecedented resolution to reveal genomic alterations driving oncogenesis in individual patients. Identifying these driver alterations through genome wide association analysis requires accurate partitioning of cell lineages based on single-cell genomic profiles, a computationally challenging problem when copy number profiles are considered. Most existing phylogenetics approaches cannot be accurately applied, as copy number alterations (CNAs) evolve under special genomic constraints and in overlapping intervals. Here, we propose a directed minimum spanning tree approach that is accurate and scalable to current single-cell datasets consisting of thousands of cells. By applying our approach on cohorts of cancer patients, we revealed novel, phenotype-associated evolutionary patterns and CNAs within and across patients.