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iMicrobe: Tools and data-dreaiven discovery platform for the microbiome sciences.
- Source :
-
GigaScience [Gigascience] 2019 Jul 01; Vol. 8 (7). - Publication Year :
- 2019
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Abstract
- Background: Scientists have amassed a wealth of microbiome datasets, making it possible to study microbes in biotic and abiotic systems on a population or planetary scale; however, this potential has not been fully realized given that the tools, datasets, and computation are available in diverse repositories and locations. To address this challenge, we developed iMicrobe.us, a community-driven microbiome data marketplace and tool exchange for users to integrate their own data and tools with those from the broader community.<br />Findings: The iMicrobe platform brings together analysis tools and microbiome datasets by leveraging National Science Foundation-supported cyberinfrastructure and computing resources from CyVerse, Agave, and XSEDE. The primary purpose of iMicrobe is to provide users with a freely available, web-based platform to (1) maintain and share project data, metadata, and analysis products, (2) search for related public datasets, and (3) use and publish bioinformatics tools that run on highly scalable computing resources. Analysis tools are implemented in containers that encapsulate complex software dependencies and run on freely available XSEDE resources via the Agave API, which can retrieve datasets from the CyVerse Data Store or any web-accessible location (e.g., FTP, HTTP).<br />Conclusions: iMicrobe promotes data integration, sharing, and community-driven tool development by making open source data and tools accessible to the research community in a web-based platform.<br /> (© The Author(s) 2019. Published by Oxford University Press.)
- Subjects :
- Big Data
Metagenome
Metagenomics methods
Microbiota genetics
Software
Subjects
Details
- Language :
- English
- ISSN :
- 2047-217X
- Volume :
- 8
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- GigaScience
- Publication Type :
- Academic Journal
- Accession number :
- 31289831
- Full Text :
- https://doi.org/10.1093/gigascience/giz083