OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data

BackgroundToday, data evaluation has become a bottleneck in chromatographic science. Analytical instruments equipped with automated samplers yield large amounts of measurement data, which needs to be verified and analyzed. Since nearly every GC/MS instrument vendor offers its own data format and software tools, the consequences are problems with data exchange and a lack of comparability between the analytical results. To challenge this situation a number of either commercial or non-profit software applications have been developed. These applications provide functionalities to import and analyze several data formats but have shortcomings in terms of the transparency of the implemented analytical algorithms and/or are restricted to a specific computer platform.ResultsThis work describes a native approach to handle chromatographic data files. The approach can be extended in its functionality such as facilities to detect baselines, to detect, integrate and identify peaks and to compare mass spectra, as well as the ability to internationalize the application. Additionally, filters can be applied on the chromatographic data to enhance its quality, for example to remove background and noise. Extended operations like do, undo and redo are supported.ConclusionsOpenChrom is a software application to edit and analyze mass spectrometric chromatographic data. It is extensible in many different ways, depending on the demands of the users or the analytical procedures and algorithms. It offers a customizable graphical user interface. The software is independent of the operating system, due to the fact that the Rich Client Platform is written in Java. OpenChrom is released under the Eclipse Public License 1.0 (EPL). There are no license constraints regarding extensions. They can be published using open source as well as proprietary licenses. OpenChrom is available free of charge at http://www.openchrom.net.

[1]  F W McLafferty,et al.  Comparison of algorithms and databases for matching unknown mass spectra , 1998, Journal of the American Society for Mass Spectrometry.

[2]  Knut Reinert,et al.  OpenMS – An open-source software framework for mass spectrometry , 2008, BMC Bioinformatics.

[3]  Xuemin Zhang,et al.  Bmc Medical Informatics and Decision Making Biosunms: a Plug-in-based Software for the Management of Patients Information and the Analysis of Peptide Profiles from Mass Spectrometry , 2009 .

[4]  D. Henneberg,et al.  Siscom — a new library search system for mass spectra , 1978 .

[5]  S. Stein,et al.  Deconvolution gas chromatography/mass spectrometry of urinary organic acids--potential for pattern recognition and automated identification of metabolic disorders. , 1999, Rapid communications in mass spectrometry : RCM.

[6]  Zeev B. Alfassi.  Vector analysis of multi-measurements identification , 2005 .

[7]  J. A. Falkner,et al.  ProteomeCommons.org IO Framework: reading and writing multiple proteomics data formats , 2007, Bioinform..

[8]  Wim G. Pool,et al.  Automated Extraction of Pure Mass Spectra from Gas Chromatographic/Mass Spectrometric Data† , 1997 .

[9]  W. Windig,et al.  A Noise and Background Reduction Method for Component Detection in Liquid Chromatography/Mass Spectrometry , 1996 .

[10]  T. Rindfleisch,et al.  Extraction of mass spectra free of background and neighboring component contributions from gas chromatography/mass spectrometry data. [for biological compounds , 1976 .

[11]  Klaus Biemann,et al.  Reconstructed Mass Spectra, A Novel Approach for the Utilization of Gas Chromatograph—Mass Spectrometer Data , 1974 .

[12]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[13]  Xin Lu,et al.  Deconvolution of overlapped peaks based on the exponentially modified Gaussian model in comprehensive two-dimensional gas chromatography. , 2005, Journal of chromatography. A.

[14]  Garrick L. Wallstrom,et al.  Measuring the effect of commuting on the performance of the Bayesian Aerosol Release Detector , 2009, BMC Medical Informatics Decis. Mak..

[15]  Jeff McAffer,et al.  Eclipse Rich Client Platform , 2010 .

[16]  S. Stein.  An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data , 1999 .

[17]  B N Colby,et al.  Spectral deconvolution for overlapping GC/MS components , 1992, Journal of the American Society for Mass Spectrometry.

[18]  Wim G. Pool,et al.  Backfolding Applied to Differential Gas Chromatography/Mass Spectrometry as a Mathematical Enhancement of Chromatographic Resolution§ , 1996 .

[19]  D. Kell,et al.  The deconvolution of pyrolysis mass spectra using genetic programming: application to the identification of some Eubacterium species. , 1998, FEMS microbiology letters.

[20]  Richard G. Brereton,et al.  Deconvolution and spectral clean-up of two-component mixtures by factor analysis of gas chromatographic–mass spectrometric data , 1996 .

[21]  Egon L. Willighagen,et al.  The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics , 2003, J. Chem. Inf. Comput. Sci..

[22]  Chris F. Taylor,et al.  A common open representation of mass spectrometry data and its application to proteomics research , 2004, Nature Biotechnology.

[23]  Fred W. McLafferty,et al.  Exact-mass probability based matching of high-resolution unknown mass spectra , 1991 .

[24]  Antony N. Davies.  The new Automated Mass Spectrometry Deconvolution and Identification System (AMDIS) , 1998 .

[25]  Z. Alfassi.  On the normalization of a mass spectrum for comparison of two spectra , 2004, Journal of the American Society for Mass Spectrometry.

[26]  Abigail Holley,et al.  Palisade Corporation , 2005, WSC '05.

[27]  Egon L. Willighagen,et al.  Bioclipse: an open source workbench for chemo- and bioinformatics , 2007, BMC Bioinformatics.

[28]  W. Windig,et al.  Chemometric analysis of complex hyphenated data. Improvements of the component detection algorithm. , 2007, Journal of chromatography. A.