ArticleBMC bioinformatics2015
Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
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- Human Adenovirus Type 55 Distribution, Regional Persistence, and Genetic Variability.Emerging infectious diseases · 2020Article
- Metagenomic Analysis Reveals Three Novel and Prevalent Mosquito Viruses from a Single Pool ofViruses · 2019Article
- Metagenomics for Clinical Infectious Disease Diagnostics Steps Closer to Reality.Journal of clinical microbiology · 2018Article
- Targeted Sequencing of Respiratory Viruses in Clinical Specimens for Pathogen Identification and Genome-Wide Analysis.Methods in molecular biology (Clifton, N.J.) · 2018Article
- Article
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Corrections and comments
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Authors and funding
24 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
resultsThe 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.
conclusionsBy 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.