ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model

oleh: Palash Sashittal, Haochen Zhang, Christine A. Iacobuzio-Donahue, Benjamin J. Raphael

Format: Article
Diterbitkan: BMC 2023-11-01

Deskripsi

Abstract A tumor contains a diverse collection of somatic mutations that reflect its past evolutionary history and that range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). However, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs, complicating the inference of tumor phylogenies. We introduce a new evolutionary model, the constrained k -Dollo model, that uses SNVs as phylogenetic markers but constrains losses of SNVs according to clusters of cells. We derive an algorithm, ConDoR, that infers phylogenies from targeted scDNA-seq data using this model. We demonstrate the advantages of ConDoR on simulated and real scDNA-seq data.