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

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

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Article number272
JournalGenome biology
Issue number1
StatePublished - Dec 2023
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Cell Biology


  • Cancer
  • Dollo model
  • Intra-tumor heterogeneity
  • Single-cell DNA sequencing
  • Tumor phylogeny


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