Implementing Data Standards: A report on the HUPOPSI Workshop September 2009, Toronto,Canada

The plenary session of the Proteomics Standards Initiative of the Human Proteome Organisation at the 8th Annual HUPO World Congress updated the delegates on the current status of the ongoing work of this group. The mass spectrometry group reviewed the progress of mzML since its release last year and detailed new work on providing a common format for SRM/MRM transition lists (TraML). The implementation of mzIdentML, for describing the output of proteomics search engines, was outlined and the release of a new web service PSICQUIC, which allows users to simultaneously search multiple interaction databases, was announced. Finally, the audience participated in a lively debate, discussing both the benefits of these standard formats and issues with their adoption and use in a research environment.     

Managing the Data Explosion A Report on the HUPO‐PSI Workshop August 2008, Amsterdam,The Netherlands

The plenary session of the Proteomics Standards Initiative (PSI) of the Human Proteome Organisation at the 7^th annual HUPO world congress updated the delegates on the current status of the ongoing work of this group. The release of the new MS interchange format, mzML, was formally announced and delegates were also updated on the advances in the area of molecular interactions, protein separations, proteomics informatics and also on PEFF, a common sequence database format currently under review in the PSI documentation process. Community input on this initiative was requested. Finally, the impact these new data standards are having on the data submission process, which increasingly is an integral part of the publication process, was reviewed and discussed.     

multiplierz: an extensible API based desktop environment for proteomics data analysis

Background  

Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge.     

Common interchange standards for proteomics data: Public availability of tools and schema

The Proteomics Standards Initiative (PSI) aims to define community standards for data representation in proteomics and to facilitate data comparision, exchange and verification. To this end, a Level 1 Molecular Interaction XML data exchange format has been developed which has been accepted for publication and is freely available at the PSI website (http.//psidev.sf.net/). Several major protein interaction databases are already making data available in this format. A draft XML interchange format for mass spectrometry data has been written and is currently undergoing evaluation whilst work is ongoing to develop a proteomics data integration model, MIAPE.     

An XML standard for the dissemination of annotated 2D gel electrophoresis data complemented with mass spectrometry results

Background  

Many proteomics initiatives require a seamless bioinformatics integration of a range of analytical steps between sample collection and systems modeling immediately assessable to the participants involved in the process. Proteomics profiling by 2D gel electrophoresis to the putative identification of differentially expressed proteins by comparison of mass spectrometry results with reference databases, includes many components of sample processing, not just analysis and interpretation, are regularly revisited and updated. In order for such updates and dissemination of data, a suitable data structure is needed. However, there are no such data structures currently available for the storing of data for multiple gels generated through a single proteomic experiments in a single XML file. This paper proposes a data structure based on XML standards to fill the void that exists between data generated by proteomics experiments and storing of data.     

PeptideDepot: Flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker‐driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end‐users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post‐acquisition analysis of proteomic data.     

A common open representation of mass spectrometry data and its application to proteomics research

A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.     

An extensible application for assembling annotation for genomic data

SUMMARY: AnnBuilder is an R package for assembling genomic annotation data. The system currently provides parsers to process annotation data from LocusLink, Gene Ontology Consortium, and Human Gene Project and can be extended to new data sources via user defined parsers. AnnBuilder differs from other existing systems in that it provides users with unlimited ability to assemble data from user selected sources. The products of AnnBuilder are files in XML format that can be easily used by different systems. AVAILABILITY: (http://www.bioconductor.org). Open source.     

Scientific workflow management in proteomics

Data processing in proteomics can be a challenging endeavor, requiring extensive knowledge of many different software packages, all with different algorithms, data format requirements, and user interfaces. In this article we describe the integration of a number of existing programs and tools in Taverna Workbench, a scientific workflow manager currently being developed in the bioinformatics community. We demonstrate how a workflow manager provides a single, visually clear and intuitive interface to complex data analysis tasks in proteomics, from raw mass spectrometry data to protein identifications and beyond.     

Enabling BioSharing - a report on the Annual Spring Workshop of the HUPO-PSI April 11-13, 2011, EMBL-Heidelberg, Germany

The Annual Spring workshop of the HUPO-PSI was this year held at the EMBL International Centre for Advanced Training (EICAT) in Heidelberg, Germany. Delegates briefly reviewed the successes of the group to date. These include the wide spread implementation of the molecular interaction data exchange formats, PSI-MI XML2.5 and MITAB, and also of mzML, the standard output format for mass spectrometer output data. These successes have resulted in enhanced accessibility to published data, for example the development of the PSICQUIC common query interface for interaction data and the development of databases such as PRIDE to act as public repositories for proteomics data and increased biosharing, through the development of consortia, for example IMEx and ProteomeXchange which will both share the burden of curating the increasing amounts of data being published and work together to make this more accessible to the bench scientist. Work then started over the three days of the workshop, with a focus on advancing the draft format for handling quantitative mass spectrometry data (mzQuantML) and further developing TraML, a standardized format for the exchange and transmission of transition lists for SRM experiments.     

Ten Years of Standardizing Proteomic Data: A Report on the HUPO-PSI Spring Workshop: April 12-14th, 2012, San Diego, USA

The Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) was established in 2002 with the aim of defining community standards for data representation in proteomics and facilitating data comparison, exchange and verification. Over the last 10 years significant advances have been made, with common data standards now published and implemented in the field of both mass spectrometry and molecular interactions. The 2012 meeting further advanced this work, with the mass spectrometry groups finalising approaches to capturing the output from recent developments in the field, such as quantitative proteomics and SRM. The molecular interaction group focused on improving the integration of data from multiple resources. Both groups united with a guest work track, organized by the HUPO Technology/Standards Committee, to formulate proposals for data submissions from the HUPO Human Proteome Project and to start an initiative to collect standard experimental protocols.     

The World-2DPAGE Constellation to promote and publish gel-based proteomics data through the ExPASy server

Since it was launched in 1993, the ExPASy server has been and is still a reference in the proteomics world. ExPASy users access various databases, many dedicated tools, and lists of resources, among other services. A significant part of resources available is devoted to two-dimensional electrophoresis data. Our latest contribution to the expansion of the pool of on-line proteomics data is the World-2DPAGE Constellation, accessible at http://world-2dpage.expasy.org/. It is composed of the established WORLD-2DPAGE List of 2-D PAGE database servers, the World-2DPAGE Portal that queries simultaneously world-wide proteomics databases, and the recently created World-2DPAGE Repository. The latter component is a public standards-compliant repository for gel-based proteomics data linked to protein identifications published in the literature. It has been set up using the Make2D-DB package, a software tool that helps building SWISS-2DPAGE-like databases on one's own Web site. The lack of necessary informatics infrastructure to build and run a dedicated website is no longer an obstacle to make proteomics data publicly accessible on the Internet.     

jmzReader: A Java parser library to process and visualize multiple text and XML-based mass spectrometry data formats

We here present the jmzReader library: a collection of Java application programming interfaces (APIs) to parse the most commonly used peak list and XML-based mass spectrometry (MS) data formats: DTA, MS2, MGF, PKL, mzXML, mzData, and mzML (based on the already existing API jmzML). The library is optimized to be used in conjunction with mzIdentML, the recently released standard data format for reporting protein and peptide identifications, developed by the HUPO proteomics standards initiative (PSI). mzIdentML files do not contain spectra data but contain references to different kinds of external MS data files. As a key functionality, all parsers implement a common interface that supports the various methods used by mzIdentML to reference external spectra. Thus, when developing software for mzIdentML, programmers no longer have to support multiple MS data file formats but only this one interface. The library (which includes a viewer) is open source and, together with detailed documentation, can be downloaded from http://code.google.com/p/jmzreader/.     

Proposal for a standard representation of two-dimensional gel electrophoresis data

The global analysis of proteins is now feasible due to improvements in techniques such as two-dimensional gel electrophoresis (2-DE), mass spectrometry, yeast two-hybrid systems and the development of bioinformatics applications. The experiments form the basis of proteomics, and present significant challenges in data analysis, storage and querying. We argue that a standard format for proteome data is required to enable the storage, exchange and subsequent re-analysis of large datasets. We describe the criteria that must be met for the development of a standard for proteomics. We have developed a model to represent data from 2-DE experiments, including difference gel electrophoresis along with image analysis and statistical analysis across multiple gels. This part of proteomics analysis is not represented in current proposals for proteomics standards. We are working with the Proteomics Standards Initiative to develop a model encompassing biological sample origin, experimental protocols, a number of separation techniques and mass spectrometry. The standard format will facilitate the development of central repositories of data, enabling results to be verified or re-analysed, and the correlation of results produced by different research groups using a variety of laboratory techniques.     

A mass spectrometry proteomics data management platform

Mass spectrometry-based proteomics is increasingly being used in biomedical research. These experiments typically generate a large volume of highly complex data, and the volume and complexity are only increasing with time. There exist many software pipelines for analyzing these data (each typically with its own file formats), and as technology improves, these file formats change and new formats are developed. Files produced from these myriad software programs may accumulate on hard disks or tape drives over time, with older files being rendered progressively more obsolete and unusable with each successive technical advancement and data format change. Although initiatives exist to standardize the file formats used in proteomics, they do not address the core failings of a file-based data management system: (1) files are typically poorly annotated experimentally, (2) files are "organically" distributed across laboratory file systems in an ad hoc manner, (3) files formats become obsolete, and (4) searching the data and comparing and contrasting results across separate experiments is very inefficient (if possible at all). Here we present a relational database architecture and accompanying web application dubbed Mass Spectrometry Data Platform that is designed to address the failings of the file-based mass spectrometry data management approach. The database is designed such that the output of disparate software pipelines may be imported into a core set of unified tables, with these core tables being extended to support data generated by specific pipelines. Because the data are unified, they may be queried, viewed, and compared across multiple experiments using a common web interface. Mass Spectrometry Data Platform is open source and freely available at http://code.google.com/p/msdapl/.     

Postexperiment monoisotopic mass filtering and refinement (PE-MMR) of tandem mass spectrometric data increases accuracy of peptide identification in LC/MS/MS

Methods for treating MS/MS data to achieve accurate peptide identification are currently the subject of much research activity. In this study we describe a new method for filtering MS/MS data and refining precursor masses that provides highly accurate analyses of massive sets of proteomics data. This method, coined "postexperiment monoisotopic mass filtering and refinement" (PE-MMR), consists of several data processing steps: 1) generation of lists of all monoisotopic masses observed in a whole LC/MS experiment, 2) clusterization of monoisotopic masses of a peptide into unique mass classes (UMCs) based on their masses and LC elution times, 3) matching the precursor masses of the MS/MS data to a representative mass of a UMC, and 4) filtration of the MS/MS data based on the presence of corresponding monoisotopic masses and refinement of the precursor ion masses by the UMC mass. PE-MMR increases the throughput of proteomics data analysis, by efficiently removing "garbage" MS/MS data prior to database searching, and improves the mass measurement accuracies (i.e. 0.05 +/- 1.49 ppm for yeast data (from 4.46 +/- 2.81 ppm) and 0.03 +/- 3.41 ppm for glycopeptide data (from 4.8 +/- 7.4 ppm)) for an increased number of identified peptides. In proteomics analyses of glycopeptide-enriched samples, PE-MMR processing greatly reduces the degree of false glycopeptide identification by correctly assigning the monoisotopic masses for the precursor ions prior to database searching. By applying this technique to analyses of proteome samples of varying complexities, we demonstrate herein that PE-MMR is an effective and accurate method for treating massive sets of proteomics data.     

APP: an Automated Proteomics Pipeline for the analysis of mass spectrometry data based on multiple open access tools

Background

Mass spectrometry analyses of complex protein samples yield large amounts of data and specific expertise is needed for data analysis, in addition to a dedicated computer infrastructure. Furthermore, the identification of proteins and their specific properties require the use of multiple independent bioinformatics tools and several database search algorithms to process the same datasets. In order to facilitate and increase the speed of data analysis, there is a need for an integrated platform that would allow a comprehensive profiling of thousands of peptides and proteins in a single process through the simultaneous exploitation of multiple complementary algorithms.

Results

We have established a new proteomics pipeline designated as APP that fulfills these objectives using a complete series of tools freely available from open sources. APP automates the processing of proteomics tasks such as peptide identification, validation and quantitation from LC-MS/MS data and allows easy integration of many separate proteomics tools. Distributed processing is at the core of APP, allowing the processing of very large datasets using any combination of Windows/Linux physical or virtual computing resources.

Conclusions

APP provides distributed computing nodes that are simple to set up, greatly relieving the need for separate IT competence when handling large datasets. The modular nature of APP allows complex workflows to be managed and distributed, speeding up throughput and setup. Additionally, APP logs execution information on all executed tasks and generated results, simplifying information management and validation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0441-8) contains supplementary material, which is available to authorized users.     

Peptide identification by tandem mass spectrometry with alternate fragmentation modes

The high-throughput nature of proteomics mass spectrometry is enabled by a productive combination of data acquisition protocols and the computational tools used to interpret the resulting spectra. One of the key components in mainstream protocols is the generation of tandem mass (MS/MS) spectra by peptide fragmentation using collision induced dissociation, the approach currently used in the large majority of proteomics experiments to routinely identify hundreds to thousands of proteins from single mass spectrometry runs. Complementary to these, alternative peptide fragmentation methods such as electron capture/transfer dissociation and higher-energy collision dissociation have consistently achieved significant improvements in the identification of certain classes of peptides, proteins, and post-translational modifications. Recognizing these advantages, mass spectrometry instruments now conveniently support fine-tuned methods that automatically alternate between peptide fragmentation modes for either different types of peptides or for acquisition of multiple MS/MS spectra from each peptide. But although these developments have the potential to substantially improve peptide identification, their routine application requires corresponding adjustments to the software tools and procedures used for automated downstream processing. This review discusses the computational implications of alternative and alternate modes of MS/MS peptide fragmentation and addresses some practical aspects of using such protocols for identification of peptides and post-translational modifications.     

GeneCruiser: a web service for the annotation of microarray data

SUMMARY: GeneCruiser is a web service allowing users to annotate their genomic data by mapping microarray feature identifiers to gene identifiers from databases, such as UniGene, while providing links to web resources, such as the UCSC Genome Browser. It relies on a regularly updated database that retrieves and indexes the mappings between microarray probes and genomic databases. Genes are identified using the Life Sciences Identifier standard. AVAILABILITY: GeneCruiser is freely available in the following forms: Web service and Web application, http://www.genecruiser.org; GenePattern, GeneCruiser access has been integrated into our microarray analysis platform, GenePattern. http://www.genepattern.org.