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Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies
Next generation sequencing technology has revolutionized the study of cancers. Through matched normal-tumor pairs, it is now possible to identify genome-wide germline and somatic mutations. The generation and analysis of the data requires rigorous quality checks and filtering, and the current analyt...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060821/ https://www.ncbi.nlm.nih.gov/pubmed/21445261 http://dx.doi.org/10.1371/journal.pone.0017810 |
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author | Goh, Liang Chen, Geng Bo Cutcutache, Ioana Low, Benjamin Teh, Bin Tean Rozen, Steve Tan, Patrick |
author_facet | Goh, Liang Chen, Geng Bo Cutcutache, Ioana Low, Benjamin Teh, Bin Tean Rozen, Steve Tan, Patrick |
author_sort | Goh, Liang |
collection | PubMed |
description | Next generation sequencing technology has revolutionized the study of cancers. Through matched normal-tumor pairs, it is now possible to identify genome-wide germline and somatic mutations. The generation and analysis of the data requires rigorous quality checks and filtering, and the current analytical pipeline is constantly undergoing improvements. We noted however that in analyzing matched pairs, there is an implicit assumption that the sequenced data are matched, without any quality check such as those implemented in association studies. There are serious implications in this assumption as identification of germline and rare somatic variants depend on the normal sample being the matched pair. Using a genetics concept on measuring relatedness between individuals, we demonstrate that the matchedness of tumor pairs can be quantified and should be included as part of a quality protocol in analysis of sequenced data. Despite the mutation changes in cancer samples, matched tumor-normal pairs are still relatively similar in sequence compared to non-matched pairs. We demonstrate that the approach can be used to assess the mutation landscape between individuals. |
format | Text |
id | pubmed-3060821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-30608212011-03-28 Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies Goh, Liang Chen, Geng Bo Cutcutache, Ioana Low, Benjamin Teh, Bin Tean Rozen, Steve Tan, Patrick PLoS One Research Article Next generation sequencing technology has revolutionized the study of cancers. Through matched normal-tumor pairs, it is now possible to identify genome-wide germline and somatic mutations. The generation and analysis of the data requires rigorous quality checks and filtering, and the current analytical pipeline is constantly undergoing improvements. We noted however that in analyzing matched pairs, there is an implicit assumption that the sequenced data are matched, without any quality check such as those implemented in association studies. There are serious implications in this assumption as identification of germline and rare somatic variants depend on the normal sample being the matched pair. Using a genetics concept on measuring relatedness between individuals, we demonstrate that the matchedness of tumor pairs can be quantified and should be included as part of a quality protocol in analysis of sequenced data. Despite the mutation changes in cancer samples, matched tumor-normal pairs are still relatively similar in sequence compared to non-matched pairs. We demonstrate that the approach can be used to assess the mutation landscape between individuals. Public Library of Science 2011-03-18 /pmc/articles/PMC3060821/ /pubmed/21445261 http://dx.doi.org/10.1371/journal.pone.0017810 Text en Goh et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Goh, Liang Chen, Geng Bo Cutcutache, Ioana Low, Benjamin Teh, Bin Tean Rozen, Steve Tan, Patrick Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies |
title | Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies |
title_full | Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies |
title_fullStr | Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies |
title_full_unstemmed | Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies |
title_short | Assessing Matched Normal and Tumor Pairs in Next-Generation Sequencing Studies |
title_sort | assessing matched normal and tumor pairs in next-generation sequencing studies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060821/ https://www.ncbi.nlm.nih.gov/pubmed/21445261 http://dx.doi.org/10.1371/journal.pone.0017810 |
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