Neha Patil (Editor)

LabKey Server

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Development status
  
Active

Operating system
  
Cross-platform

Written in
  
Java

License
  
Apache License 2.0

Developer(s)
  
LabKey Software Foundation

Stable release
  
16.3 / November 14, 2016; 3 months ago (2016-11-14)

LabKey Server is free, open source software available for scientists to integrate, analyze, and share biomedical research data. The platform provides a secure data repository that allows web-based querying, reporting, and collaborating across a range of data sources. Specific scientific applications and workflows can be added on top of the basic platform and leverage a data processing pipeline.

Contents

License

LabKey licenses LabKey Server and its documentation for free under the Apache License.

Languages and extensibility

The base platform is written in Java. It can be extended through the addition of Java-based modules or simple, file-based modules written in HTML, XML and JavaScript. The platform can also be extended using LabKey Server's Java, JavaScript, R, Python, Perl and SAS client libraries.

History

LabKey Server, originally known as the Computational Proteomics Analysis System (CPAS), was developed at the Fred Hutchinson Cancer Research Center to manage high volumes of data generated at the Fred Hutch Computational Proteomics Lab. In 2005, a small team spun out of the Hutch and began operating independently as LabKey Software after contributors realized that the software could be beneficial to the broader scientific community.

Core Components

LabKey Server provides a secure data repository for all types of biomedical data, including mass spectrometry, flow cytometry, microarray, microplate, ELISpot, ELISA, NAb and observational study information. A customizable data processing pipeline allows the upload and processing of the large data files common in biomedical research.

The platform also provides domain-specific support for several areas of research, including:

  • Observational Studies. Supports management of longitudinal, large-scale studies of participants, subjects or animals over time. Allows the integration of clinical data with assay results.
  • Proteomics. Allows the processing of high-throughput mass spectrometry data using tools such as the X! Tandem search engine, the Trans-Proteomic Pipeline, Mascot and Sequest. Certified as "Silver-Level Compliant Data Service" with the caBIG standard.
  • Flow Cytometry. Supports automated quality control, centralized data management and web-based data sharing. Integrates with FlowJo.

    • Zika Open Research Portal

    In 2016, LabKey and Professor Dave O'Connor of the University of Wisconsin–Madison launched the Zika Open Research Portal [1] using LabKey Server. The portal provides direct access to experiment data being produced by members of the Zika Experimental Science Team (ZEST). The portal received attention from the scientific community for being the first platform of its kind to share real-time research data.

    Users

    Users range from individual labs to large research consortia. In 2010, the program's users included the following:

  • Fred Hutchinson Cancer Research Center
  • Statistical Center for HIV/AIDS Research and Prevention (SCHARP)
  • Center for HIV-AIDS Vaccine Immunology (CHAVI) at Duke University
  • Collaboration for AIDS Vaccine Discovery (CAVD), funded by the Gates Foundation
  • Wisconsin National Primate Research Center
  • International AIDS Vaccine Initiative (IAVI)
  • Infectious Disease Research Institute (IDRI)
  • Cedars-Sinai Medical Center
  • Institute of Molecular and Cell Biology (Singapore)
  • NIMML
  • Harvard Partners
  • University of Washington
  • University of Michigan
  • University of Kentucky
  • University of Wisconsin

    • Publications

  • Nelson, Elizabeth K; Piehler, Britt; Eckels, Josh; Rauch, Adam; Bellew, Matthew; Hussey, Peter; Ramsay, Sarah; Nathe, Cory; Lum, Karl; Krouse, Kevin; Stearns, David; Connolly, Brian; Skillman, Tom; Igra, Mark (2011). "LabKey Server: An open source platform for scientific data integration, analysis and collaboration". BMC Bioinformatics. 12: 71. doi:10.1186/1471-2105-12-71. PMC 3062597. PMID 21385461. 
  • Rauch, Adam; Bellew, Matthew; Eng, Jimmy; Fitzgibbon, Matthew; Holzman, Ted; Hussey, Peter; Igra, Mark; MacLean, Brendan; et al. (2006). "Computational Proteomics Analysis System (CPAS): An Extensible, Open-Source Analytic System for Evaluating and Publishing Proteomic Data and High Throughput Biological Experiments". Journal of Proteome Research. 5 (1): 112–21. doi:10.1021/pr0503533. PMID 16396501. 
  • Shulman, Nicholas; Bellew, Matthew; Snelling, George; Carter, Donald; Huang, Yunda; Li, Hongli; Self, Steven G.; McElrath, M. Juliana; De Rosa, Stephen C. (2008). "Development of an automated analysis system for data from flow cytometric intracellular cytokine staining assays from clinical vaccine trials". Cytometry Part A. 73A (9): 847. doi:10.1002/cyto.a.20600. 
  • "The Best of Both Worlds: Integrating a Java Web Application with SAS Using the SAS/SHARE Driver for JDBC" (PDF). 

    • References

    LabKey Server Wikipedia
    (Text) CC BY-SA


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