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Cpipe: a shared variant detection pipeline designed for diagnostic settings
The benefits of implementing high throughput sequencing in the clinic are quickly becoming apparent. However, few freely available bioinformatics pipelines have been built from the ground up with clinical genomics in mind. Here we present Cpipe, a pipeline designed specifically for clinical genetic...
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/PMC4515933/ https://www.ncbi.nlm.nih.gov/pubmed/26217397 http://dx.doi.org/10.1186/s13073-015-0191-x |
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author | Sadedin, Simon P. Dashnow, Harriet James, Paul A. Bahlo, Melanie Bauer, Denis C. Lonie, Andrew Lunke, Sebastian Macciocca, Ivan Ross, Jason P. Siemering, Kirby R. Stark, Zornitza White, Susan M. Taylor, Graham Gaff, Clara Oshlack, Alicia Thorne, Natalie P. |
author_facet | Sadedin, Simon P. Dashnow, Harriet James, Paul A. Bahlo, Melanie Bauer, Denis C. Lonie, Andrew Lunke, Sebastian Macciocca, Ivan Ross, Jason P. Siemering, Kirby R. Stark, Zornitza White, Susan M. Taylor, Graham Gaff, Clara Oshlack, Alicia Thorne, Natalie P. |
author_sort | Sadedin, Simon P. |
collection | PubMed |
description | The benefits of implementing high throughput sequencing in the clinic are quickly becoming apparent. However, few freely available bioinformatics pipelines have been built from the ground up with clinical genomics in mind. Here we present Cpipe, a pipeline designed specifically for clinical genetic disease diagnostics. Cpipe was developed by the Melbourne Genomics Health Alliance, an Australian initiative to promote common approaches to genomics across healthcare institutions. As such, Cpipe has been designed to provide fast, effective and reproducible analysis, while also being highly flexible and customisable to meet the individual needs of diverse clinical settings. Cpipe is being shared with the clinical sequencing community as an open source project and is available at http://cpipeline.org. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-015-0191-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4515933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45159332015-07-28 Cpipe: a shared variant detection pipeline designed for diagnostic settings Sadedin, Simon P. Dashnow, Harriet James, Paul A. Bahlo, Melanie Bauer, Denis C. Lonie, Andrew Lunke, Sebastian Macciocca, Ivan Ross, Jason P. Siemering, Kirby R. Stark, Zornitza White, Susan M. Taylor, Graham Gaff, Clara Oshlack, Alicia Thorne, Natalie P. Genome Med Software The benefits of implementing high throughput sequencing in the clinic are quickly becoming apparent. However, few freely available bioinformatics pipelines have been built from the ground up with clinical genomics in mind. Here we present Cpipe, a pipeline designed specifically for clinical genetic disease diagnostics. Cpipe was developed by the Melbourne Genomics Health Alliance, an Australian initiative to promote common approaches to genomics across healthcare institutions. As such, Cpipe has been designed to provide fast, effective and reproducible analysis, while also being highly flexible and customisable to meet the individual needs of diverse clinical settings. Cpipe is being shared with the clinical sequencing community as an open source project and is available at http://cpipeline.org. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-015-0191-x) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-10 /pmc/articles/PMC4515933/ /pubmed/26217397 http://dx.doi.org/10.1186/s13073-015-0191-x Text en © Sadedin et al. 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 Sadedin, Simon P. Dashnow, Harriet James, Paul A. Bahlo, Melanie Bauer, Denis C. Lonie, Andrew Lunke, Sebastian Macciocca, Ivan Ross, Jason P. Siemering, Kirby R. Stark, Zornitza White, Susan M. Taylor, Graham Gaff, Clara Oshlack, Alicia Thorne, Natalie P. Cpipe: a shared variant detection pipeline designed for diagnostic settings |
title | Cpipe: a shared variant detection pipeline designed for diagnostic settings |
title_full | Cpipe: a shared variant detection pipeline designed for diagnostic settings |
title_fullStr | Cpipe: a shared variant detection pipeline designed for diagnostic settings |
title_full_unstemmed | Cpipe: a shared variant detection pipeline designed for diagnostic settings |
title_short | Cpipe: a shared variant detection pipeline designed for diagnostic settings |
title_sort | cpipe: a shared variant detection pipeline designed for diagnostic settings |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4515933/ https://www.ncbi.nlm.nih.gov/pubmed/26217397 http://dx.doi.org/10.1186/s13073-015-0191-x |
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