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 Contact: mmcintos@fhcrc.org Supplementary Information: Supplementary materials are available at (select ‘Published Experiments’ from the list of Projects and then ‘msInspect Paper’).
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.
BackgroundBroad-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.ResultsTo 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.ConclusionsSharing 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.
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. ' (1), and the other the flow cytometric assay referred to as intracellular cytokine staining (ICS) (2), both of which enumerate antigen-specific cytokine-producing T cells. The ICS assay provides more information than the ELISpot assay, because it identifies CD41 or CD81 responding cells and can examine multiple cytokines. When used in clinical HIV vaccine trials, the assays provide information about the immunogenicity of the regimen, which then guides decisions about proceeding to large-scale efficacy trials. Thus, standardized and validated assays performed in the good laboratory practices (GLP) setting are necessary to ensure accurate immunogenicity assessment.As more vaccines are developed and advanced for clinical evaluation, the increased number of complex data from ICS assays demands implementation of high-throughput analyses. The flow-based ICS assay requires a specialized analysis involving calculation of compensation for each data set, sequential gating and quality assessment. Because of the large number of assays performed daily, manual analysis and quality assessment for each data set are not feasible. Therefore, to address this
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