OncoNEM: inferring tumor evolution from single-cell sequencing data. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Ross, Edith; Markowetz, Florian
• Is Part Of: Genome biology. Volume 17:Issue 1(2016)
• Page Start: 1
• Page End: 14
• Publication Date: 2016-12
• Subjects: Tumor evolution -- Cancer evolution -- Tumor heterogeneity -- Single-cell sequencing -- Phylogenetic tree; Genomes -- Periodicals; Biology -- Periodicals; Molecular biology -- Periodicals; 572.8633
• DOI: 10.1186/s13059-016-0929-9
• Languages: English
• ISSNs: 1474-760X

Abstract

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.