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1.
Curr Protoc Bioinformatics ; Chapter 13: 13.5.1-13.5.25, 2011 Dec.
Article in English | MEDLINE | ID: mdl-22161569

ABSTRACT

LabKey Server (formerly CPAS, the Computational Proteomics Analysis System) provides a Web-based platform for mining data from liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic experiments. This open source platform supports systematic proteomic analyses and secure data management, integration, and sharing. LabKey Server incorporates several tools currently used in proteomic analysis, including the X! Tandem search engine, the ProteoWizard toolkit, and the PeptideProphet and ProteinProphet data mining tools. These tools and others are integrated into LabKey Server, which provides an extensible architecture for developing high-throughput biological applications. The LabKey Server analysis pipeline acts on data in standardized file formats, so that researchers may use LabKey Server with other search engines, including Mascot or SEQUEST, that follow a standardized format for reporting search engine results. Supported builds of LabKey Server are freely available at http://www.labkey.com/. Documentation and source code are available under the Apache License 2.0 at http://www.labkey.org.


Subject(s)
Proteomics/methods , Software , Chromatography, Liquid/methods , Data Mining , Databases, Protein , Mass Spectrometry/methods , Proteomics/instrumentation
2.
BMC Bioinformatics ; 12: 71, 2011 Mar 09.
Article in English | MEDLINE | ID: mdl-21385461

ABSTRACT

BACKGROUND: Broad-based collaborations are becoming increasingly common among disease researchers. For example, the Global HIV Enterprise has united cross-disciplinary consortia to speed progress towards HIV vaccines through coordinated research across the boundaries of institutions, continents and specialties. New, end-to-end software tools for data and specimen management are necessary to achieve the ambitious goals of such alliances. These tools must enable researchers to organize and integrate heterogeneous data early in the discovery process, standardize processes, gain new insights into pooled data and collaborate securely. RESULTS: To meet these needs, we enhanced the LabKey Server platform, formerly known as CPAS. This freely available, open source software is maintained by professional engineers who use commercially proven practices for software development and maintenance. Recent enhancements support: (i) Submitting specimens requests across collaborating organizations (ii) Graphically defining new experimental data types, metadata and wizards for data collection (iii) Transitioning experimental results from a multiplicity of spreadsheets to custom tables in a shared database (iv) Securely organizing, integrating, analyzing, visualizing and sharing diverse data types, from clinical records to specimens to complex assays (v) Interacting dynamically with external data sources (vi) Tracking study participants and cohorts over time (vii) Developing custom interfaces using client libraries (viii) Authoring custom visualizations in a built-in R scripting environment. Diverse research organizations have adopted and adapted LabKey Server, including consortia within the Global HIV Enterprise. Atlas is an installation of LabKey Server that has been tailored to serve these consortia. It is in production use and demonstrates the core capabilities of LabKey Server. Atlas now has over 2,800 active user accounts originating from approximately 36 countries and 350 organizations. It tracks roughly 27,000 assay runs, 860,000 specimen vials and 1,300,000 vial transfers. CONCLUSIONS: Sharing data, analysis tools and infrastructure can speed the efforts of large research consortia by enhancing efficiency and enabling new insights. The Atlas installation of LabKey Server demonstrates the utility of the LabKey platform for collaborative research. Stable, supported builds of LabKey Server are freely available for download at http://www.labkey.org. Documentation and source code are available under the Apache License 2.0.


Subject(s)
Database Management Systems , Databases, Factual , Information Dissemination/methods , Software , Computational Biology , Cooperative Behavior , Internet
3.
Cytometry A ; 73(9): 847-56, 2008 Sep.
Article in English | MEDLINE | ID: mdl-18615598

ABSTRACT

Intracellular cytokine staining (ICS) by multiparameter flow cytometry is one of the primary methods for determining T-cell immunogenicity in HIV-1 clinical vaccine trials. Data analysis requires considerable expertise and time. The amount of data is quickly increasing as more and larger trials are performed, and thus there is a critical need for high-throughput methods of data analysis. A web-based flow cytometric analysis system, LabKey Flow, was developed for the analyses of data from standardized ICS assays. Using a gating template created manually in commercially available flow cytometric analysis software, the system automatically compensates and analyzes all data sets. Quality control queries were designed to identify potentially incorrect sample collections. Comparison of the semiautomated analysis performed by LabKey Flow and the manual analysis performed using FlowJo software demonstrated excellent concordance (concordance correlation coefficient > 0.990). Manual inspection of the analyses performed by LabKey Flow for eight-color ICS data files from several clinical vaccine trials indicated that template gates can appropriately be used for most data sets. Thus, the semiautomated LabKey Flow analysis system can accurately analyze large ICS data files. Routine use of the system does not require specialized expertise. This high-throughput analysis will provide great utility for rapid evaluation of complex multiparameter flow cytometric measurements collected from large clinical trials.


Subject(s)
AIDS Vaccines/immunology , Cytokines/analysis , Flow Cytometry , Internet , Software , AIDS Vaccines/therapeutic use , CD4-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/immunology , Cells, Cultured , Clinical Trials as Topic , Cytoplasm/immunology , Data Interpretation, Statistical , HIV Infections/drug therapy , HIV-1 , Humans , Quality Control
4.
Bioinformatics ; 22(15): 1902-9, 2006 Aug 01.
Article in English | MEDLINE | ID: mdl-16766559

ABSTRACT

MOTIVATION: Comparing two or more complex protein mixtures using liquid chromatography mass spectrometry (LC-MS) requires multiple analysis steps to locate and quantitate natural peptides within a single experiment and to align and normalize findings across multiple experiments. RESULTS: We describe msInspect, an open-source application comprising algorithms and visualization tools for the analysis of multiple LC-MS experimental measurements. The platform integrates novel algorithms for detecting signatures of natural peptides within a single LC-MS measurement and combines multiple experimental measurements into a peptide array, which may then be mined using analysis tools traditionally applied to genomic array analysis. The platform supports quantitation by both label-free and isotopic labeling approaches. The software implementation has been designed so that many key components may be easily replaced, making it useful as a workbench for integrating other novel algorithms developed by a growing research community. AVAILABILITY: The msInspect software is distributed freely under an Apache 2.0 license. The software as well as a Zip file with all peptide feature files and scripts needed to generate the tables and figures in this article are available at http://proteomics.fhcrc.org/.


Subject(s)
Algorithms , Chromatography, Liquid/methods , Mass Spectrometry/methods , Peptide Mapping/methods , Proteins/analysis , Proteins/chemistry , Software , User-Computer Interface , Complex Mixtures/analysis , Computer Graphics , Systems Integration
5.
J Proteome Res ; 5(1): 112-21, 2006 Jan.
Article in English | MEDLINE | ID: mdl-16396501

ABSTRACT

The open-source Computational Proteomics Analysis System (CPAS) contains an entire data analysis and management pipeline for Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) proteomics, including experiment annotation, protein database searching and sequence management, and mining LC-MS/MS peptide and protein identifications. CPAS architecture and features, such as a general experiment annotation component, installation software, and data security management, make it useful for collaborative projects across geographical locations and for proteomics laboratories without substantial computational support.


Subject(s)
Computational Biology/methods , Database Management Systems , Proteomics/methods
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