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

OncoNEM: inferring tumor evolution from single-cell sequencing data.

Author information

1
Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, UK.
2
Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, UK. florian.markowetz@cruk.cam.ac.uk.

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

PMID:
27083415
PMCID:
PMC4832472
DOI:
10.1186/s13059-016-0929-9
[Indexed for MEDLINE]
Free PMC Article

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