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

Genome Biol. 2023 Nov 30;24(1):272. doi: 10.1186/s13059-023-03106-5.

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.

Keywords: Cancer; Dollo model; Intra-tumor heterogeneity; Single-cell DNA sequencing; Tumor phylogeny.

MeSH terms

  • Algorithms
  • Animals
  • Birds / genetics
  • DNA Copy Number Variations
  • Humans
  • Mutation
  • Neoplasms* / genetics
  • Phylogeny
  • Sequence Analysis, DNA