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Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline
BACKGROUND: In the past decade, bioinformatics tools have matured enough to reliably perform sophisticated primary data analysis on Next Generation Sequencing (NGS) data, such as mapping, assemblies and variant calling, however, there is still a dire need for improvements in the higher level analysi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680031/ https://www.ncbi.nlm.nih.gov/pubmed/23714400 http://dx.doi.org/10.1186/1471-2105-14-167 |
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author | Hadj Khodabakhshi, Alireza Fejes, Anthony P Birol, Inanc Jones, Steven JM |
author_facet | Hadj Khodabakhshi, Alireza Fejes, Anthony P Birol, Inanc Jones, Steven JM |
author_sort | Hadj Khodabakhshi, Alireza |
collection | PubMed |
description | BACKGROUND: In the past decade, bioinformatics tools have matured enough to reliably perform sophisticated primary data analysis on Next Generation Sequencing (NGS) data, such as mapping, assemblies and variant calling, however, there is still a dire need for improvements in the higher level analysis such as NGS data organization, analysis of mutation patterns and Genome Wide Association Studies (GWAS). RESULTS: We present a high throughput pipeline for identifying cancer mutation targets, capable of processing billions of variations across thousands of samples. This pipeline is coupled with our Human Variation Database to provide more complex down stream analysis on the variations hosted in the database. Most notably, these analysis include finding significantly mutated regions across multiple genomes and regions with mutational preferences within certain types of cancers. The results of the analysis is presented in HTML summary reports that incorporate gene annotations from various resources for the reported regions. CONCLUSION: MuteProc is available for download through the Vancouver Short Read Analysis Package on Sourceforge: http://vancouvershortr.sourceforge.net. Instructions for use and a tutorial are provided on the accompanying wiki pages at https://sourceforge.net/apps/mediawiki/vancouvershortr/index.php?title=Pipeline_introduction. |
format | Online Article Text |
id | pubmed-3680031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36800312013-06-13 Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline Hadj Khodabakhshi, Alireza Fejes, Anthony P Birol, Inanc Jones, Steven JM BMC Bioinformatics Methodology Article BACKGROUND: In the past decade, bioinformatics tools have matured enough to reliably perform sophisticated primary data analysis on Next Generation Sequencing (NGS) data, such as mapping, assemblies and variant calling, however, there is still a dire need for improvements in the higher level analysis such as NGS data organization, analysis of mutation patterns and Genome Wide Association Studies (GWAS). RESULTS: We present a high throughput pipeline for identifying cancer mutation targets, capable of processing billions of variations across thousands of samples. This pipeline is coupled with our Human Variation Database to provide more complex down stream analysis on the variations hosted in the database. Most notably, these analysis include finding significantly mutated regions across multiple genomes and regions with mutational preferences within certain types of cancers. The results of the analysis is presented in HTML summary reports that incorporate gene annotations from various resources for the reported regions. CONCLUSION: MuteProc is available for download through the Vancouver Short Read Analysis Package on Sourceforge: http://vancouvershortr.sourceforge.net. Instructions for use and a tutorial are provided on the accompanying wiki pages at https://sourceforge.net/apps/mediawiki/vancouvershortr/index.php?title=Pipeline_introduction. BioMed Central 2013-05-28 /pmc/articles/PMC3680031/ /pubmed/23714400 http://dx.doi.org/10.1186/1471-2105-14-167 Text en Copyright © 2013 Hadj Khodabakhshi et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Article Hadj Khodabakhshi, Alireza Fejes, Anthony P Birol, Inanc Jones, Steven JM Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline |
title | Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline |
title_full | Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline |
title_fullStr | Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline |
title_full_unstemmed | Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline |
title_short | Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline |
title_sort | identifying cancer mutation targets across thousands of samples: muteproc, a high throughput mutation analysis pipeline |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680031/ https://www.ncbi.nlm.nih.gov/pubmed/23714400 http://dx.doi.org/10.1186/1471-2105-14-167 |
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