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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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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. |
format | Online Article Text |
id | pubmed-4832472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT rossedithm onconeminferringtumorevolutionfromsinglecellsequencingdata AT markowetzflorian onconeminferringtumorevolutionfromsinglecellsequencingdata |