OncoNEM: inferring tumor evolution from single-cell sequencing data

Genome Biol. 2016 Apr 15;17:69. doi: 10.1186/s13059-016-0929-9.

Abstract

Single-cell sequencing promises a high-resolution view of genetic heterogeneity and clonal evolution in cancer. However, methods to infer tumor evolution from single-cell sequencing data lag behind methods developed for bulk-sequencing data. Here, we present OncoNEM, a probabilistic method for inferring intra-tumor evolutionary lineage trees from somatic single nucleotide variants of single cells. OncoNEM identifies homogeneous cellular subpopulations and infers their genotypes as well as a tree describing their evolutionary relationships. In simulation studies, we assess OncoNEM's robustness and benchmark its performance against competing methods. Finally, we show its applicability in case studies of muscle-invasive bladder cancer and essential thrombocythemia.

Keywords: Cancer evolution; Phylogenetic tree; Single-cell sequencing; Tumor evolution; Tumor heterogeneity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Clonal Evolution
  • Computational Biology / methods*
  • Evolution, Molecular
  • Genotype
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Models, Statistical
  • Phylogeny
  • Polymorphism, Single Nucleotide
  • Single-Cell Analysis / methods*
  • Thrombocytopenia / genetics*
  • Urinary Bladder Neoplasms / genetics*