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SCNVSim: somatic copy number variation and structure variation simulator
BACKGROUND: Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteri...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349766/ https://www.ncbi.nlm.nih.gov/pubmed/25886838 http://dx.doi.org/10.1186/s12859-015-0502-7 |
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author | Qin, Maochun Liu, Biao Conroy, Jeffrey M Morrison, Carl D Hu, Qiang Cheng, Yubo Murakami, Mitsuko Odunsi, Adekunle O Johnson, Candace S Wei, Lei Liu, Song Wang, Jianmin |
author_facet | Qin, Maochun Liu, Biao Conroy, Jeffrey M Morrison, Carl D Hu, Qiang Cheng, Yubo Murakami, Mitsuko Odunsi, Adekunle O Johnson, Candace S Wei, Lei Liu, Song Wang, Jianmin |
author_sort | Qin, Maochun |
collection | PubMed |
description | BACKGROUND: Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods. RESULTS: SCNVSim is a tool for simulating somatic CNVs and structure variations SVs. Other than multiple types of SV and CNV events, the tool is capable of simulating important features related to tumor samples including aneuploidy, heterogeneity and purity. CONCLUSIONS: SCNVSim generates the genomes of a cancer cell population with detailed information of copy number status, loss of heterozygosity (LOH), and event break points, which is essential for developing and evaluating somatic CNV and SV detection methods in cancer genomics studies. |
format | Online Article Text |
id | pubmed-4349766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43497662015-03-06 SCNVSim: somatic copy number variation and structure variation simulator Qin, Maochun Liu, Biao Conroy, Jeffrey M Morrison, Carl D Hu, Qiang Cheng, Yubo Murakami, Mitsuko Odunsi, Adekunle O Johnson, Candace S Wei, Lei Liu, Song Wang, Jianmin BMC Bioinformatics Software BACKGROUND: Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods. RESULTS: SCNVSim is a tool for simulating somatic CNVs and structure variations SVs. Other than multiple types of SV and CNV events, the tool is capable of simulating important features related to tumor samples including aneuploidy, heterogeneity and purity. CONCLUSIONS: SCNVSim generates the genomes of a cancer cell population with detailed information of copy number status, loss of heterozygosity (LOH), and event break points, which is essential for developing and evaluating somatic CNV and SV detection methods in cancer genomics studies. BioMed Central 2015-02-28 /pmc/articles/PMC4349766/ /pubmed/25886838 http://dx.doi.org/10.1186/s12859-015-0502-7 Text en © Qin et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 | Software Qin, Maochun Liu, Biao Conroy, Jeffrey M Morrison, Carl D Hu, Qiang Cheng, Yubo Murakami, Mitsuko Odunsi, Adekunle O Johnson, Candace S Wei, Lei Liu, Song Wang, Jianmin SCNVSim: somatic copy number variation and structure variation simulator |
title | SCNVSim: somatic copy number variation and structure variation simulator |
title_full | SCNVSim: somatic copy number variation and structure variation simulator |
title_fullStr | SCNVSim: somatic copy number variation and structure variation simulator |
title_full_unstemmed | SCNVSim: somatic copy number variation and structure variation simulator |
title_short | SCNVSim: somatic copy number variation and structure variation simulator |
title_sort | scnvsim: somatic copy number variation and structure variation simulator |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349766/ https://www.ncbi.nlm.nih.gov/pubmed/25886838 http://dx.doi.org/10.1186/s12859-015-0502-7 |
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