Fast and Efficient XML Data Access for Next-Generation Mass Spectrometry

Motivation

In mass spectrometry-based proteomics, XML formats such as mzML and mzXML provide an open and standardized way to store and exchange the raw data (spectra and chromatograms) of mass spectrometric experiments. These file formats are being used by a multitude of open-source and cross-platform tools which allow the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis. Recent improvements in mass spectrometry instrumentation have increased the data size produced in a single LC-MS/MS measurement and put substantial strain on open-source tools, particularly those that are not equipped to deal with XML data files that reach dozens of gigabytes in size.

Results

Here we present a fast and versatile parsing library for mass spectrometric XML formats available in C++ and Python, based on the mature OpenMS software framework. Our library implements an API for obtaining spectra and chromatograms under memory constraints using random access or sequential access functions, allowing users to process datasets that are much larger than system memory. For fast access to the raw data structures, small XML files can also be completely loaded into memory. In addition, we have improved the parsing speed of the core mzML module by over 4-fold (compared to OpenMS 1.11), making our library suitable for a wide variety of algorithms that need fast access to dozens of gigabytes of raw mass spectrometric data.

Availability

Our C++ and Python implementations are available for the Linux, Mac, and Windows operating systems. All proposed modifications to the OpenMS code have been merged into the OpenMS mainline codebase and are available to the community at https://github.com/OpenMS/OpenMS.     

Transparent mediation-based access to multiple yeast data sources using an ontology driven interface

BACKGROUND: Saccharomyces cerevisiae is recognized as a model system representing a simple eukaryote whose genome can be easily manipulated. Information solicited by scientists on its biological entities (Proteins, Genes, RNAs...) is scattered within several data sources like SGD, Yeastract, CYGD-MIPS, BioGrid, PhosphoGrid, etc. Because of the heterogeneity of these sources, querying them separately and then manually combining the returned results is a complex and time-consuming task for biologists most of whom are not bioinformatics expert. It also reduces and limits the use that can be made on the available data. RESULTS: To provide transparent and simultaneous access to yeast sources, we have developed YeastMed: an XML and mediator-based system. In this paper, we present our approach in developing this system which takes advantage of SB-KOM to perform the query transformation needed and a set of Data Services to reach the integrated data sources. The system is composed of a set of modules that depend heavily on XML and Semantic Web technologies. User queries are expressed in terms of a domain ontology through a simple form-based web interface. CONCLUSIONS: YeastMed is the first mediation-based system specific for integrating yeast data sources. It was conceived mainly to help biologists to find simultaneously relevant data from multiple data sources. It has a biologist-friendly interface easy to use. The system is available at http://www.khaos.uma.es/yeastmed/.     

An ontology driven architecture for derived representations of macromolecular structure

SUMMARY: An object metamodel based on a standard scientific ontology has been developed and used to generate a CORBA interface, an SQL schema and an XML representation for macromolecular structure (MMS) data. In addition to the interface and schema definitions, the metamodel was also used to generate the core elements of a CORBA reference server and a JDBC database loader. The Java source code which implements this metamodel, the CORBA server, database loader and XML converter along with detailed documentation and code examples are available as part of the OpenMMS toolkit. AVAILABILITY: http://openmms.sdsc.edu CONTACT: dsg@sdsc.edu     

A flexible online metadata editing and management system

Our team developed a metadata editing and management system employing state of the art XML technologies initially aimed at the environmental sciences but with the potential to be useful across multiple domains. We chose a modular and distributed design for scalability, flexibility, options for customizations, and the possibility to add more functionality at a later stage. The system consists of a desktop design tool that generates code for the actual online editor, a native XML database, and an online user access management application. A Java Swing application that reads an XML schema, the design tool provides the designer with options to combine input fields into online forms with user-friendly tags and determine the flow of input forms. Based on design decisions, the tool generates XForm code for the online metadata editor which is based on the Orbeon XForms engine. The design tool fulfills two requirements: First data entry forms based on a schema are customized at design time and second the tool can generate data entry applications for any valid XML schema without relying on custom information in the schema. A configuration file in the design tool saves custom information generated at design time. Future developments will add functionality to the design tool to integrate help text, tool tips, project specific keyword lists, and thesaurus services.Cascading style sheets customize the look-and-feel of the finished editor. The editor produces XML files in compliance with the original schema, however, a user may save the input into a native XML database at any time independent of validity. The system uses the open source XML database eXist for storage and uses a MySQL relational database and a simple Java Server Faces user interface for file and access management. We chose three levels to distribute administrative responsibilities and handle the common situation of an information manager entering the bulk of the metadata but leave specifics to the actual data provider.     

XEMBL: distributing EMBL data in XML format

Data in the EMBL Nucleotide Sequence Database is traditionally available in a flat file format that has a number of known shortcomings. With XML rapidly emerging as a standard data exchange format that can address some problems of flat file formats by defining data structure and syntax, there is now a demand to distribute EMBL data in an XML format. XEMBL is a service tool that employs CORBA servers to access EMBL data, and distributes the data in XML format via a number of mechanisms. AVAILABILITY: Use of the XEMBL service is free of charge at http://www.ebi.ac.uk/xembl/, and can be accessed via web forms, CGI, and a SOAP-enabled service. SUPPLEMENTARY INFORMATION: Information on the EMBL Nucleotide Sequence Database is available at http://www.ebi.ac.uk/embl/. The EMBL Object Model is available at http://corba.ebi.ac.uk/models/. Information on the EMBL CORBA servers is at http://corba.ebi.ac.uk/     

Bioinformatics visualization and integration with open standards: the Bluejay genomic browser

We have created a new Java-based integrated computational environment for the exploration of genomic data, called Bluejay. The system is capable of using almost any XML file related to genomic data. Non-XML data sources can be accessed via a proxy server. Bluejay has several features, which are new to Bioinformatics, including an unlimited semantic zoom capability, coupled with Scalable Vector Graphics (SVG) outputs; an implementation of the XLink standard, which features access to MAGPIE Genecards as well as any BioMOBY service accessible over the Internet; and the integration of gene chip analysis tools with the functional assignments. The system can be used as a signed web applet, Web Start, and a local stand-alone application, with or without connection to the Internet. It is available free of charge and as open source via http://bluejay.ucalgary.ca.     

IPeak: An open source tool to combine results from multiple MS/MS search engines

Liquid chromatography coupled tandem mass spectrometry (LC‐MS/MS) is an important technique for detecting peptides in proteomics studies. Here, we present an open source software tool, termed IPeak, a peptide identification pipeline that is designed to combine the Percolator post‐processing algorithm and multi‐search strategy to enhance the sensitivity of peptide identifications without compromising accuracy. IPeak provides a graphical user interface (GUI) as well as a command‐line interface, which is implemented in JAVA and can work on all three major operating system platforms: Windows, Linux/Unix and OS X. IPeak has been designed to work with the mzIdentML standard from the Proteomics Standards Initiative (PSI) as an input and output, and also been fully integrated into the associated mzidLibrary project, providing access to the overall pipeline, as well as modules for calling Percolator on individual search engine result files. The integration thus enables IPeak (and Percolator) to be used in conjunction with any software packages implementing the mzIdentML data standard. IPeak is freely available and can be downloaded under an Apache 2.0 license at https://code.google.com/p/mzidentml‐lib/ .     

pyOpenMS: A Python‐based interface to the OpenMS mass‐spectrometry algorithm library

pyOpenMS is an open‐source, Python‐based interface to the C++ OpenMS library, providing facile access to a feature‐rich, open‐source algorithm library for MS‐based proteomics analysis. It contains Python bindings that allow raw access to the data structures and algorithms implemented in OpenMS, specifically those for file access (mzXML, mzML, TraML, mzIdentML among others), basic signal processing (smoothing, filtering, de‐isotoping, and peak‐picking) and complex data analysis (including label‐free, SILAC, iTRAQ, and SWATH analysis tools). pyOpenMS thus allows fast prototyping and efficient workflow development in a fully interactive manner (using the interactive Python interpreter) and is also ideally suited for researchers not proficient in C++. In addition, our code to wrap a complex C++ library is completely open‐source, allowing other projects to create similar bindings with ease. The pyOpenMS framework is freely available at https://pypi.python.org/pypi/pyopenms while the autowrap tool to create Cython code automatically is available at https://pypi.python.org/pypi/autowrap (both released under the 3‐clause BSD licence).     

CADB: Conformation Angles DataBase of proteins

Conformation Angles DataBase (CADB) provides an online resource to access data on conformation angles (both main-chain and side-chain) of protein structures in two data sets corresponding to 25% and 90% sequence identity between any two proteins, available in the Protein Data Bank. In addition, the database contains the necessary crystallographic parameters. The package has several flexible options and display facilities to visualize the main-chain and side-chain conformation angles for a particular amino acid residue. The package can also be used to study the interrelationship between the main-chain and side-chain conformation angles. A web based JAVA graphics interface has been deployed to display the user interested information on the client machine. The database is being updated at regular intervals and can be accessed over the World Wide Web interface at the following URL: http://144.16.71.148/cadb/.     

XML, bioinformatics and data integration

Motivation: The eXtensible Markup Language (XML) is an emerging standard for structuring documents, notably for the World Wide Web. In this paper, the authors present XML and examine its use as a data language for bioinformatics. In particular, XML is compared to other languages, and some of the potential uses of XML in bioinformatics applications are presented. The authors propose to adopt XML for data interchange between databases and other sources of data. Finally the discussion is illustrated by a test case of a pedigree data model in XML. Contact: Emmanuel.Barillot@infobiogen.fr     

MADGE: scalable distributed data management software for cDNA microarrays

MOTIVATION: The human genome project and the development of new high-throughput technologies have created unparalleled opportunities to study the mechanism of diseases, monitor the disease progression and evaluate effective therapies. Gene expression profiling is a critical tool to accomplish these goals. The use of nucleic acid microarrays to assess the gene expression of thousands of genes simultaneously has seen phenomenal growth over the past five years. Although commercial sources of microarrays exist, investigators wanting more flexibility in the genes represented on the array will turn to in-house production. The creation and use of cDNA microarrays is a complicated process that generates an enormous amount of information. Effective data management of this information is essential to efficiently access, analyze, troubleshoot and evaluate the microarray experiments. RESULTS: We have developed a distributable software package designed to track and store the various pieces of data generated by a cDNA microarray facility. This includes the clone collection storage data, annotation data, workflow queues, microarray data, data repositories, sample submission information, and project/investigator information. This application was designed using a 3-tier client server model. The data access layer (1st tier) contains the relational database system tuned to support a large number of transactions. The data services layer (2nd tier) is a distributed COM server with full database transaction support. The application layer (3rd tier) is an internet based user interface that contains both client and server side code for dynamic interactions with the user. AVAILABILITY: This software is freely available to academic institutions and non-profit organizations at http://www.genomics.mcg.edu/niddkbtc.     

caBIONet--A .NET wrapper to access and process genomic data stored at the National Cancer Institute's Center for Bioinformatics databases

MOTIVATION: The National Cancer Institute's Center for Bioinformatics (NCICB) has developed a Java based data management and information system called caCORE. One component of this software suite is the object oriented API (caBIO) used to access the rich biological datasets collected at the NCI. This API can access the data using native Java classes, SOAP requests or HTTP calls. Non-Java based clients wanting to use this API have to use the SOAP or HTTP interfaces with the data being returned from the NCI servers as an XML data stream. Although the XML can be read and manipulated using DOM or SAX parsers, one loses the convenience and usability of an object oriented programming paradigm. caBIONet is a set of .NET wrapper classes (managers, genes, chromosomes, sequences, etc.) capable of serializing the XML data stream into local .NET objects. The software is able to search NCICB databases and provide local objects representing the data that can be manipulated and used by other .NET programs. The software was written in C# and compiled as a .NET DLL.     

jmzIdentML API: A Java interface to the mzIdentML standard for peptide and protein identification data

We present a Java application programming interface (API), jmzIdentML, for the Human Proteome Organisation (HUPO) Proteomics Standards Initiative (PSI) mzIdentML standard for peptide and protein identification data. The API combines the power of Java Architecture of XML Binding (JAXB) and an XPath-based random-access indexer to allow a fast and efficient mapping of extensible markup language (XML) elements to Java objects. The internal references in the mzIdentML files are resolved in an on-demand manner, where the whole file is accessed as a random-access swap file, and only the relevant piece of XMLis selected for mapping to its corresponding Java object. The APIis highly efficient in its memory usage and can handle files of arbitrary sizes. The APIfollows the official release of the mzIdentML (version 1.1) specifications and is available in the public domain under a permissive licence at http://www.code.google.com/p/jmzidentml/.     

MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data

Protein identification using MS is an important technique in proteomics as well as a major generator of proteomics data. We have designed the protein identification data object model (PDOM) and developed a parser based on this model to facilitate the analysis and storage of these data. The parser works with HTML or XML files saved or exported from MASCOT MS/MS ions search in peptide summary report or MASCOT PMF search in protein summary report. The program creates PDOM objects, eliminates redundancy in the input file, and has the capability to output any PDOM object to a relational database. This program facilitates additional analysis of MASCOT search results and aids the storage of protein identification information. The implementation is extensible and can serve as a template to develop parsers for other search engines. The parser can be used as a stand-alone application or can be driven by other Java programs. It is currently being used as the front end for a system that loads HTML and XML result files of MASCOT searches into a relational database. The source code is freely available at http://www.ccbm.jhu.edu and the program uses only free and open-source Java libraries.     

The PSI semantic validator: A framework to check MIAPE compliance of proteomics data

The Human Proteome Organization's Proteomics Standards Initiative (PSI) promotes the development of exchange standards to improve data integration and interoperability. PSI specifies the suitable level of detail required when reporting a proteomics experiment (via the Minimum Information About a Proteomics Experiment), and provides extensible markup language (XML) exchange formats and dedicated controlled vocabularies (CVs) that must be combined to generate a standard compliant document. The framework presented here tackles the issue of checking that experimental data reported using a specific format, CVs and public bio‐ontologies (e.g. Gene Ontology, NCBI taxonomy) are compliant with the Minimum Information About a Proteomics Experiment recommendations. The semantic validator not only checks the XML syntax but it also enforces rules regarding the use of an ontology class or CV terms by checking that the terms exist in the resource and that they are used in the correct location of a document. Moreover, this framework is extremely fast, even on sizable data files, and flexible, as it can be adapted to any standard by customizing the parameters it requires: an XML Schema Definition, one or more CVs or ontologies, and a mapping file describing in a formal way how the semantic resources and the format are interrelated. As such, the validator provides a general solution to the common problem in data exchange: how to validate the correct usage of a data standard beyond simple XML Schema Definition validation. The framework source code and its various applications can be found at http://psidev.info/validator .     

SAmBA: An interactive software for optimizing the design of biological macromolecules crystallization experiments

SAmBA is a new software for the design of minimal experimental protocols using the notion of orthogonal arrays of strength 2. The main application of SAmBA is the search of protein crystallization conditions. Given a user input defining the relevant effectors/variables (e.g., pH, temperature, salts) and states (e.g., pH: 5, 6, 7 and 8), this software proposes an optimal set of experiments in which all tested variables and the pairwise interactions between them are symmetrically sampled. No a priori restrictions on the number and range of experimental variables is imposed. SAmBA consists of two complementary programs, SAm and BA, using a simulated annealing approach and a backtracking algorithm, respectively. The software is freely available as C code or as an interactive JAVA applet at http://igs-server.cnrs-mrs.fr . Proteins 29:252–257, 1997. © 1997 Wiley-Liss, Inc.     

CRAVE: a database, middleware and visualization system for phenotype ontologies

MOTIVATION: A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. RESULTS: CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.