Bioinformatics Advance Access originally published online on October 6, 2009
Bioinformatics 2009 25(23):3128-3134; doi:10.1093/bioinformatics/btp568
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Qupe—a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments
1 Computational Genomics, Center for Biotechnology (CeBiTec), 2 Biodata Mining & Applied Neuroinformatics Group, Faculty of Technology, Bielefeld University, Bielefeld, 3 Biomolecular Mass Spectrometry, Department of Analytical Chemistry, 4 Plant Biochemistry, Faculty of Biology and Biotechnology, Ruhr-University Bochum, 5 Institute for Genome Research and Systems Biology (IGS) and 6 Bioinformatics Resource Facility, CeBiTec, Bielefeld University, Bielefeld, Germany
* To whom correspondence should be addressed.
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Abstract |
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Motivation: The goal of present -omics sciences is to understand biological systems as a whole in terms of interactions of the individual cellular components. One of the main building blocks in this field of study is proteomics where tandem mass spectrometry (LC-MS/MS) in combination with isotopic labelling techniques provides a common way to obtain a direct insight into regulation at the protein level. Methods to identify and quantify the peptides contained in a sample are well established, and their output usually results in lists of identified proteins and calculated relative abundance values. The next step is to move ahead from these abstract lists and apply statistical inference methods to compare measurements, to identify genes that are significantly up- or down-regulated, or to detect clusters of proteins with similar expression profiles.
Results: We introduce the Rich Internet Application (RIA) Qupe providing comprehensive data management and analysis functions for LC-MS/MS experiments. Starting with the import of mass spectra data the system guides the experimenter through the process of protein identification by database search, the calculation of protein abundance ratios, and in particular, the statistical evaluation of the quantification results including multivariate analysis methods such as analysis of variance or hierarchical cluster analysis. While a data model to store these results has been developed, a well-defined programming interface facilitates the integration of novel approaches. A compute cluster is utilized to distribute computationally intensive calculations, and a web service allows to interchange information with other -omics software applications. To demonstrate that Qupe represents a step forward in quantitative proteomics analysis an application study on Corynebacterium glutamicum has been carried out.
Availability and Implementation: Qupe is implemented in Java utilizing Hibernate, Echo2, R and the Spring framework. We encourage the usage of the RIA in the sense of the ‘software as a service’ concept, maintained on our servers and accessible at the following location: http://qupe.cebitec.uni-bielefeld.de
Contact: stefan.albaum{at}cebitec.uni-bielefeld.de
Supplementary information: Supplementary data are available at Bioinformatics online.
Received on July 16, 2009; revised on September 11, 2009; accepted on September 28, 2009
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