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OncoNEM: inferring tumor evolution from single-cell sequencing data

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 infer...

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Detalles Bibliográficos
Autores principales: Ross, Edith M., Markowetz, Florian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832472/
https://www.ncbi.nlm.nih.gov/pubmed/27083415
http://dx.doi.org/10.1186/s13059-016-0929-9
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author Ross, Edith M.
Markowetz, Florian
author_facet Ross, Edith M.
Markowetz, Florian
author_sort Ross, Edith M.
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-0929-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-48324722016-04-16 OncoNEM: inferring tumor evolution from single-cell sequencing data Ross, Edith M. Markowetz, Florian Genome Biol Method 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-0929-9) contains supplementary material, which is available to authorized users. BioMed Central 2016-04-15 /pmc/articles/PMC4832472/ /pubmed/27083415 http://dx.doi.org/10.1186/s13059-016-0929-9 Text en © Ross and Markowetz. 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Ross, Edith M.
Markowetz, Florian
OncoNEM: inferring tumor evolution from single-cell sequencing data
title OncoNEM: inferring tumor evolution from single-cell sequencing data
title_full OncoNEM: inferring tumor evolution from single-cell sequencing data
title_fullStr OncoNEM: inferring tumor evolution from single-cell sequencing data
title_full_unstemmed OncoNEM: inferring tumor evolution from single-cell sequencing data
title_short OncoNEM: inferring tumor evolution from single-cell sequencing data
title_sort onconem: inferring tumor evolution from single-cell sequencing data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832472/
https://www.ncbi.nlm.nih.gov/pubmed/27083415
http://dx.doi.org/10.1186/s13059-016-0929-9
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