SPhyR: Tumor phylogeny estimation from single-cell sequencing data under loss and error

Research output: Contribution to journalArticlepeer-review

Abstract

Motivation Cancer is characterized by intra-tumor heterogeneity, the presence of distinct cell populations with distinct complements of somatic mutations, which include single-nucleotide variants (SNVs) and copy-number aberrations (CNAs). Single-cell sequencing technology enables one to study these cell populations at single-cell resolution. Phylogeny estimation algorithms that employ appropriate evolutionary models are key to understanding the evolutionary mechanisms behind intra-tumor heterogeneity. Results We introduce Single-cell Phylogeny Reconstruction (SPhyR), a method for tumor phylogeny estimation from single-cell sequencing data. In light of frequent loss of SNVs due to CNAs in cancer, SPhyR employs the k-Dollo evolutionary model, where a mutation can only be gained once but lost k times. Underlying SPhyR is a novel combinatorial characterization of solutions as constrained integer matrix completions, based on a connection to the cladistic multi-state perfect phylogeny problem. SPhyR outperforms existing methods on simulated data and on a metastatic colorectal cancer. Availability and implementation SPhyR is available on https://github.com/elkebir-group/SPhyR. Supplementary information Supplementary data are available at Bioinformatics online.

Original languageEnglish (US)
Pages (from-to)i671-i679
JournalBioinformatics
Volume34
Issue number17
DOIs
StatePublished - Sep 1 2018

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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