Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2, and characterize protein complexes3. Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access4,5. In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.

Panorama is a web application for storing, sharing, analyzing, and reusing targeted assays created and refined with Skyline,1 an increasingly popular Windows client software tool for targeted proteomics experiments. Panorama allows laboratories to store and organize curated results contained in Skyline documents with fine-grained permissions, which facilitates distributed collaboration and secure sharing of published and unpublished data via a web-browser interface. It is fully integrated with the Skyline workflow and supports publishing a document directly to a Panorama server from the Skyline user interface. Panorama captures the complete Skyline document information content in a relational database schema. Curated results published to Panorama can be aggregated and exported as chromatogram libraries. These libraries can be used in Skyline to pick optimal targets in new experiments and to validate peak identification of target peptides. Panorama is open-source and freely available. It is distributed as part of LabKey Server,2 an open source biomedical research data management system. Laboratories and organizations can set up Panorama locally by downloading and installing the software on their own servers. They can also request freely hosted projects on , a Panorama server maintained by the Department of Genome Sciences at the University of Washington.

To address the growing need for a centralized, community resource of published results processed with Skyline, and to provide reviewers and readers immediate visual access to the data behind published conclusions, we present Panorama Public (https://panoramaweb.org/public.url), a repository of Skyline documents supporting published results. Panorama Public is built on Panorama, an open source data management system for mass spectrometry data processed with the Skyline targeted mass spectrometry environment. The Panorama web application facilitates viewing, sharing, and disseminating results contained in Skyline documents via a web-browser. Skyline users can easily upload their documents to a Panorama server and allow other researchers to explore uploaded results in the Panorama web-interface through a variety of familiar summary graphs as well as annotated views of the chromatographic peaks processed with Skyline. This makes Panorama ideal for sharing targeted, quantitative results contained in Skyline documents with collaborators, reviewers, and the larger proteomics community. The Panorama Public repository employs the full data visualization capabilities of Panorama which facilitates sharing results with reviewers during manuscript review.

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.

We report the development of a completely automated pipeline to monitor system suitability in bottom-up proteomic experiments. LC MS/MS runs are automatically imported into Skyline and multiple identification free metrics are extracted from targeted peptides. These data are then uploaded to the Panorama Skyline document repository where metrics can be viewed in a web based interface using powerful process control techniques, including Levey-Jennings and Pareto plots. The interface is versatile and takes user input which allows the user significant control over the visualization of the data. The pipeline is vendor and instrument type neutral, supports multiple acquisition techniques (e.g. MS 1 filtering, data independent acquisition, parallel reaction monitoring, and selected reaction monitoring), can track performance of multiple instruments, and requires no manual intervention aside from initial setup. Data can be viewed from any computer with internet access and a web browser -- facilitating sharing of QC data between researchers. Herein we describe the use of this pipeline, termed Panorama AutoQC, to evaluate LC MS/MS performance in a range of scenarios from identification of suboptimal instrument performance, evaluation of ultra-high pressure chromatography, to the identification of the major sources of variation throughout years of peptide data collection.