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A three-caller pipeline for variant analysis of cancer whole-exome sequencing data
Rapid advancements in next generation sequencing (NGS) technologies, coupled with the dramatic decrease in cost, have made NGS one of the leading approaches applied in cancer research. In addition, it is increasingly used in clinical practice for cancer diagnosis and treatment. Somatic (cancer-only)...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428716/ https://www.ncbi.nlm.nih.gov/pubmed/28447726 http://dx.doi.org/10.3892/mmr.2017.6336 |
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author | Liu, Ze-Kun Shang, Yu-Kui Chen, Zhi-Nan Bian, Huijie |
author_facet | Liu, Ze-Kun Shang, Yu-Kui Chen, Zhi-Nan Bian, Huijie |
author_sort | Liu, Ze-Kun |
collection | PubMed |
description | Rapid advancements in next generation sequencing (NGS) technologies, coupled with the dramatic decrease in cost, have made NGS one of the leading approaches applied in cancer research. In addition, it is increasingly used in clinical practice for cancer diagnosis and treatment. Somatic (cancer-only) single nucleotide variants and small insertions and deletions (indels) are the simplest classes of mutation, however, their identification in whole exome sequencing data is complicated by germline polymorphisms, tumor heterogeneity and errors in sequencing and analysis. An increasing number of software and methodological guidelines are being published for the analysis of sequencing data. Usually, the algorithms of MuTect, VarScan and Genome Analysis Toolkit are applied to identify the variants. However, one of these algorithms alone results in incomplete genomic information. To address this issue, the present study developed a systematic pipeline for analyzing the whole exome sequencing data of hepatocellular carcinoma (HCC) using a combination of the three algorithms, named the three-caller pipeline. Application of the three-caller pipeline to the whole exome data of HCC, improved the detection of true positive mutations and a total of 75 tumor-specific somatic variants were identified. Functional enrichment analysis revealed the mutations in the genes encoding cell adhesion and regulation of Ras GTPase activity. This pipeline provides an effective approach to identify variants from NGS data for subsequent functional analyses. |
format | Online Article Text |
id | pubmed-5428716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-54287162017-05-15 A three-caller pipeline for variant analysis of cancer whole-exome sequencing data Liu, Ze-Kun Shang, Yu-Kui Chen, Zhi-Nan Bian, Huijie Mol Med Rep Articles Rapid advancements in next generation sequencing (NGS) technologies, coupled with the dramatic decrease in cost, have made NGS one of the leading approaches applied in cancer research. In addition, it is increasingly used in clinical practice for cancer diagnosis and treatment. Somatic (cancer-only) single nucleotide variants and small insertions and deletions (indels) are the simplest classes of mutation, however, their identification in whole exome sequencing data is complicated by germline polymorphisms, tumor heterogeneity and errors in sequencing and analysis. An increasing number of software and methodological guidelines are being published for the analysis of sequencing data. Usually, the algorithms of MuTect, VarScan and Genome Analysis Toolkit are applied to identify the variants. However, one of these algorithms alone results in incomplete genomic information. To address this issue, the present study developed a systematic pipeline for analyzing the whole exome sequencing data of hepatocellular carcinoma (HCC) using a combination of the three algorithms, named the three-caller pipeline. Application of the three-caller pipeline to the whole exome data of HCC, improved the detection of true positive mutations and a total of 75 tumor-specific somatic variants were identified. Functional enrichment analysis revealed the mutations in the genes encoding cell adhesion and regulation of Ras GTPase activity. This pipeline provides an effective approach to identify variants from NGS data for subsequent functional analyses. D.A. Spandidos 2017-05 2017-03-16 /pmc/articles/PMC5428716/ /pubmed/28447726 http://dx.doi.org/10.3892/mmr.2017.6336 Text en Copyright: © Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Liu, Ze-Kun Shang, Yu-Kui Chen, Zhi-Nan Bian, Huijie A three-caller pipeline for variant analysis of cancer whole-exome sequencing data |
title | A three-caller pipeline for variant analysis of cancer whole-exome sequencing data |
title_full | A three-caller pipeline for variant analysis of cancer whole-exome sequencing data |
title_fullStr | A three-caller pipeline for variant analysis of cancer whole-exome sequencing data |
title_full_unstemmed | A three-caller pipeline for variant analysis of cancer whole-exome sequencing data |
title_short | A three-caller pipeline for variant analysis of cancer whole-exome sequencing data |
title_sort | three-caller pipeline for variant analysis of cancer whole-exome sequencing data |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428716/ https://www.ncbi.nlm.nih.gov/pubmed/28447726 http://dx.doi.org/10.3892/mmr.2017.6336 |
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