Jose Ángel Dianes

ProteomeXchange provides globally coordinated proteomics data submission and dissemination

5. Tools available and ways to submit data to PX ............................................................. 11 5.1. MS/MS data submissions to PRIDE .................................................................................... 11 5.1.1. Creation of supported files for “Complete” submissions .................................................. 11 5.1.1.1. PRIDE XML .................................................................................................................................. 11 5.1.1.2. mzIdentML ................................................................................................................................. 13 5.1.2. Checking the files before submission (initial quality assessment) ..................................... 14 5.1.3. File submission to PRIDE: the PX submission tool ............................................................. 15 5.1.3.1. General Information ................................................................................................................... 15 5.1.3.2. Functionality, Design and Implementation Details .................................................................... 15 5.1.3.3. New open source libraries made available with PX submission tool ......................................... 18 5.1.3.4. PX Submission Tool Java Web Start ............................................................................................ 18 5.1.4. File submission to PRIDE: Command line support using Aspera ........................................ 19 5.1.5. Examples of Partial submissions to PRIDE ......................................................................... 19 5.2. SRM data submissions via PASSEL ..................................................................................... 20

The Proteomics Identifications (PRIDE) database and associated tools: status in 2013

The PRoteomics IDEntifications (PRIDE, http://www.ebi.ac.uk/pride) database at the European Bioinformatics Institute is one of the most prominent data repositories of mass spectrometry (MS)-based proteomics data. Here, we summarize recent developments in the PRIDE database and related tools. First, we provide up-to-date statistics in data content, splitting the figures by groups of organisms and species, including peptide and protein identifications, and post-translational modifications. We then describe the tools that are part of the PRIDE submission pipeline, especially the recently developed PRIDE Converter 2 (new submission tool) and PRIDE Inspector (visualization and analysis tool). We also give an update about the integration of PRIDE with other MS proteomics resources in the context of the ProteomeXchange consortium. Finally, we briefly review the quality control efforts that are ongoing at present and outline our future plans.

2016 update of the PRIDE database and its related tools

The PRoteomics IDEntifications (PRIDE) database is one of the world-leading data repositories of mass spectrometry (MS)-based proteomics data. Since the beginning of 2014, PRIDE Archive (http://www.ebi.ac.uk/pride/archive/) is the new PRIDE archival system, replacing the original PRIDE database. Here we summarize the developments in PRIDE resources and related tools since the previous update manuscript in the Database Issue in 2013. PRIDE Archive constitutes a complete redevelopment of the original PRIDE, comprising a new storage backend, data submission system and web interface, among other components. PRIDE Archive supports the most-widely used PSI (Proteomics Standards Initiative) data standard formats (mzML and mzIdentML) and implements the data requirements and guidelines of the ProteomeXchange Consortium. The wide adoption of ProteomeXchange within the community has triggered an unprecedented increase in the number of submitted data sets (around 150 data sets per month). We outline some statistics on the current PRIDE Archive data contents. We also report on the status of the PRIDE related stand-alone tools: PRIDE Inspector, PRIDE Converter 2 and the ProteomeXchange submission tool. Finally, we will give a brief update on the resources under development ‘PRIDE Cluster’ and ‘PRIDE Proteomes’, which provide a complementary view and quality-scored information of the peptide and protein identification data available in PRIDE Archive.

The PRoteomics IDEntification (PRIDE) Converter 2 Framework: An Improved Suite of Tools to Facilitate Data Submission to the PRIDE Database and the ProteomeXchange Consortium

The original PRIDE Converter tool greatly simplified the process of submitting mass spectrometry (MS)-based proteomics data to the PRIDE database. However, after much user feedback, it was noted that the tool had some limitations and could not handle several user requirements that were now becoming commonplace. This prompted us to design and implement a whole new suite of tools that would build on the successes of the original PRIDE Converter and allow users to generate submission-ready, well-annotated PRIDE XML files. The PRIDE Converter 2 tool suite allows users to convert search result files into PRIDE XML (the format needed for performing submissions to the PRIDE database), generate mzTab skeleton files that can be used as a basis to submit quantitative and gel-based MS data, and post-process PRIDE XML files by filtering out contaminants and empty spectra, or by merging several PRIDE XML files together. All the tools have both a graphical user interface that provides a dialog-based, user-friendly way to convert and prepare files for submission, as well as a command-line interface that can be used to integrate the tools into existing or novel pipelines, for batch processing and power users. The PRIDE Converter 2 tool suite will thus become a cornerstone in the submission process to PRIDE and, by extension, to the ProteomeXchange consortium of MS-proteomics data repositories.

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average, 75% of spectra analyzed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large scale to shed light on these unidentified spectra. The Proteomics Identifications (PRIDE) Database Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in the PRIDE Archive, coming from hundreds of data sets, we were able to consistently characterize spectra into three distinct groups: (1) incorrectly identified, (2) correctly identified but below the set scoring threshold, and (3) truly unidentified. Using multiple complementary analysis approaches, we were able to identify ∼20% of the consistently unidentified spectra. The complete spectrum-clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.

PRIDE Inspector Toolsuite: Moving Toward a Universal Visualization Tool for Proteomics Data Standard Formats and Quality Assessment of ProteomeXchange Datasets

The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE. The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX “complete” submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/.

Providing temporal isolation in the OSGi framework

The OSGi Framework is a run-time environment for deploying service-containing Java components. Dynamically reconfigurable Java applications can be developed through the Frameworks powerful capabilities such as installing, uninstalling, updating components at run-time, and allowing the substitution of service implementations at run-time. Coupled with the capability to be remotely managed, the OSGi Framework is proving a success in a variety of application domains. One domain where it is yet to make an impact is real-time systems. Despite the fact that OSGi components and services can be developed using the Real-Time Specification for Java (RTSJ), there are still a variety of problems preventing the use of the Framework to develop real-time systems. One such problem is a lack of temporal isolation. This paper focuses on how temporal isolation can be provided in the OSGi Framework as a first step towards using the Framework to developing real-time systems with the RTSJ.

ServiceDDS: A Framework for Real-Time P2P Systems Integration

In recent times real-time distributed systems have definitively become peer-to-peer organized. The common interactions are those of different real-time components dealing with sensors or actuators, implementing controllers, performing monitoring and surveillance tasks, and interacting between them in a dynamic decentralized way. There is a need for mechanisms that allow the integration of these independent components, saving development time while keeping their real-time capability. Services and events, thanks to their decoupled nature are perfect candidates for supporting these architectures. The data centric approach goes even farther, introducing a global data space that allows a flexible, decoupled and scalable coordination environment over which services and events can be added as specific interactions mechanisms inside this global data space, in order to support all the architectural possibilities. The Data Distribution Service specification provides a totally decentralized data-centric approach with real-time quality of service support. It is a perfect base upon which to develop a framework for the integration of real-time distributed architectures.

Using standards to integrate soft real-time components into dynamic distributed architectures

A pervasive application domain today is one in which independently developed real-time components participate in a dynamic and decentralized way from distributed environments. Several challenges arise from this domain, related with participant heterogeneity, transient behavior, scalability or quality of service. The use of standards is important here, where a multidiscipline approach is required. We propose ServiceDDS, a framework that combines different standard technologies to solve the problems related with the integration of components into the described environment. ServiceDDS is based on DDS to support dynamic distributed interactions, XMPP to provide Web access, and RTSJ for real-time performance.

Towards memory management for service-oriented real-time systems

Dynamically discoverable units of software (services) are the centerpiece of service-oriented architecture (SOA). Such dynamic software architectures closely match the dynamics of businesses, and for that reason, SOA is becoming an increasingly important approach to the development of software. However, one aspect of deploying such dynamic software, that is frequently neglected, is the impact that it has on the availability of hardware resources such as CPU utilization and memory consumption. All software systems require the system load to be controlled in order to provide the service user with some level of quality-of-service. Furthermore, one type of software, which is particularly difficult to develop and would certainly benefit from the use of service-orientation, is real-time systems. Such systems, however, require resource guarantees and therefore are currently prohibited from using service-orientation in their design. In this paper we propose solutions to the problems relating to providing memory management in service-oriented real-time systems (RT-SOA).