OncoNEM: inferring tumor evolution from single-cell sequencing data
Open Access
- 15 April 2016
- journal article
- research article
- Published by Springer Science and Business Media LLC in Genome Biology
- Vol. 17 (1), 1-14
- https://doi.org/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.Funding Information
- Cancer Research UK (C14303/A17197)
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