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Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform

BACKGROUND: The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based op...

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Autores principales: Kilianski, Andy, Carcel, Patrick, Yao, Shijie, Roth, Pierce, Schulte, Josh, Donarum, Greg B., Fochler, Ed T., Hill, Jessica M., Liem, Alvin T., Wiley, Michael R., Ladner, Jason T., Pfeffer, Bradley P., Elliot, Oliver, Petrosov, Alexandra, Jima, Dereje D., Vallard, Tyghe G., Melendrez, Melanie C., Skowronski, Evan, Quan, Phenix-Lan, Lipkin, W. Ian, Gibbons, Henry S., Hirschberg, David L., Palacios, Gustavo F., Rosenzweig, C. Nicole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4696252/
https://www.ncbi.nlm.nih.gov/pubmed/26714571
http://dx.doi.org/10.1186/s12859-015-0840-5
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author Kilianski, Andy
Carcel, Patrick
Yao, Shijie
Roth, Pierce
Schulte, Josh
Donarum, Greg B.
Fochler, Ed T.
Hill, Jessica M.
Liem, Alvin T.
Wiley, Michael R.
Ladner, Jason T.
Pfeffer, Bradley P.
Elliot, Oliver
Petrosov, Alexandra
Jima, Dereje D.
Vallard, Tyghe G.
Melendrez, Melanie C.
Skowronski, Evan
Quan, Phenix-Lan
Lipkin, W. Ian
Gibbons, Henry S.
Hirschberg, David L.
Palacios, Gustavo F.
Rosenzweig, C. Nicole
author_facet Kilianski, Andy
Carcel, Patrick
Yao, Shijie
Roth, Pierce
Schulte, Josh
Donarum, Greg B.
Fochler, Ed T.
Hill, Jessica M.
Liem, Alvin T.
Wiley, Michael R.
Ladner, Jason T.
Pfeffer, Bradley P.
Elliot, Oliver
Petrosov, Alexandra
Jima, Dereje D.
Vallard, Tyghe G.
Melendrez, Melanie C.
Skowronski, Evan
Quan, Phenix-Lan
Lipkin, W. Ian
Gibbons, Henry S.
Hirschberg, David L.
Palacios, Gustavo F.
Rosenzweig, C. Nicole
author_sort Kilianski, Andy
collection PubMed
description BACKGROUND: The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. RESULTS: The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. CONCLUSIONS: By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0840-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-46962522015-12-31 Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform Kilianski, Andy Carcel, Patrick Yao, Shijie Roth, Pierce Schulte, Josh Donarum, Greg B. Fochler, Ed T. Hill, Jessica M. Liem, Alvin T. Wiley, Michael R. Ladner, Jason T. Pfeffer, Bradley P. Elliot, Oliver Petrosov, Alexandra Jima, Dereje D. Vallard, Tyghe G. Melendrez, Melanie C. Skowronski, Evan Quan, Phenix-Lan Lipkin, W. Ian Gibbons, Henry S. Hirschberg, David L. Palacios, Gustavo F. Rosenzweig, C. Nicole BMC Bioinformatics Software BACKGROUND: The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. RESULTS: The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. CONCLUSIONS: By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0840-5) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-29 /pmc/articles/PMC4696252/ /pubmed/26714571 http://dx.doi.org/10.1186/s12859-015-0840-5 Text en © Kilianski et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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
Kilianski, Andy
Carcel, Patrick
Yao, Shijie
Roth, Pierce
Schulte, Josh
Donarum, Greg B.
Fochler, Ed T.
Hill, Jessica M.
Liem, Alvin T.
Wiley, Michael R.
Ladner, Jason T.
Pfeffer, Bradley P.
Elliot, Oliver
Petrosov, Alexandra
Jima, Dereje D.
Vallard, Tyghe G.
Melendrez, Melanie C.
Skowronski, Evan
Quan, Phenix-Lan
Lipkin, W. Ian
Gibbons, Henry S.
Hirschberg, David L.
Palacios, Gustavo F.
Rosenzweig, C. Nicole
Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
title Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
title_full Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
title_fullStr Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
title_full_unstemmed Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
title_short Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
title_sort pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4696252/
https://www.ncbi.nlm.nih.gov/pubmed/26714571
http://dx.doi.org/10.1186/s12859-015-0840-5
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