Difference between revisions of "Journal:OpenChrom: A cross-platform open source software for the mass spectrometric analysis of chromatographic data"

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==Background==
==Background==
Software has become an integral part of analysis techniques. Especially in the area of gas chromatography/mass spectrometry, automatic samplers enable high throughput analyses. Software assists handling large amounts of data generated by automated and fast operating analytical instruments. Modern computer systems are inexpensive, powerful and allow analysis techniques that could not have been applied in the past. Deconvolution, a chromatographic quality enhancing technique, demonstrates for instance that increasing processor power makes new analysis techniques applicable. The technique of deconvolution has been described by Biller and Biemann<ref name="BillerIdent77">{{cite journal |title=Identification of the components of complex mixtures by GC-MS |journal=Abstracts Of Papers Of The American Chemical Society |author=Biller, J.E.; Herlihy, W.C.; Biemann, K. |volume=173 |issue=MAR20 |pages=23–23 |year=1977 |url=http://pubs.acs.org/doi/abs/10.1021/bk-1977-0054.ch002}}</ref><ref name="BillerRecon74">{{cite journal |title=Reconstructed Mass Spectra, A Novel Approach for the Utilization of Gas Chromatograph—Mass Spectrometer Data |journal=Analytical Letters |author=Biller, J.E.; Biemann, K. |volume=7 |issue=7 |pages=515–528 |year=1974 |doi=10.1080/00032717408058783}}</ref>, Dromey et al.<ref name="FromeyExtract76">{{cite journal |title=Extraction of mass spectra free of background and neighboring component contributions from gas chromatography/mass spectrometry data |journal=Analytical Chemistry |author=Dromey, R.G.; Stefik, M.J.; Rindfleisch, T.C.; Duffield, A.M. |volume=48 |issue=9 |pages=1368–1375 |year=1976 |doi=10.1021/ac50003a027}}</ref>, Colby<ref name="ColbySpect92">{{cite journal |title=Spectral deconvolution for overlapping GC/MS components |journal=Journal of the American Society for Mass Spectrometry |author=Colby, B.N. |volume=3 |issue=5 |pages=558–562 |year=1992 |doi=10.1016/1044-0305(92)85033-G |pmid=24234499}}</ref>, Hindmarch et al.<ref name="HindmarchDecon96">{{cite journal |title=Deconvolution and spectral clean-up of two-component mixtures by factor analysis of gas chromatographic–mass spectrometric data |journal=Analyst |author=Hindmarch, P.; Demir, C.; Brereton, R.G. |volume=121 |issue=8 |pages=993-1001 |year=1996 |doi=10.1039/AN9962100993}}</ref>, Halket et al.<ref name="HalketDecon99">{{cite journal |title=Deconvolution gas chromatography/mass spectrometry of urinary organic acids – potential for pattern recognition and automated identification of metabolic disorders |journal=Rapid Communications In Mass Spectrometry |author=Halket, J.M.; Przyborowska, A.; Stein, S.E. et al. |volume=13 |issue=4 |pages=279–284 |year=1999 |doi=10.1002/(SICI)1097-0231(19990228)13:4<279::AID-RCM478>3.0.CO;2-I |pmid=10097403}}</ref>, Kong et al.<ref name="KongDecon05">{{cite journal |title=Deconvolution of overlapped peaks based on the exponentially modified Gaussian model in comprehensive two-dimensional gas chromatography |journal=Journal of Chromatography A |author=Kong, H.W.; Ye, F.; Lu, X.; Guo, L.; Tian, J.; Xu, G.W. |volume=1086 |issue=1–2 |pages=160–164 |year=2005 |doi=10.1016/j.chroma.2005.05.103 |pmid=16130668}}</ref>, Taylor et al.<ref name="TaylorTheDecon98">{{cite journal |title=The deconvolution of pyrolysis mass spectra using genetic programming: Application to the identification of some ''Eubacterium'' species |journal=FEMS Microbiology Letters |author=Taylor, J.; Goodacre, R.; Wade, W.G. |volume=160 |issue=2 |pages=237–246 |year=1998 |doi=10.1111/j.1574-6968.1998.tb12917.x |pmid=9532743}}</ref>, Pool et al.<ref name="PoolBack96">{{cite journal |title=Backfolding applied to differential gas chromatography/mass spectrometry as a mathematical enhancement of chromatographic resolution |journal=Journal Of Mass Spectrometry |author=Pool, W.G.; deLeeuw, J.W.; vandeGraaf, B. |volume=31 |issue=5 |pages=509–516 |year=1996 |doi=10.1002/(SICI)1096-9888(199605)31:5<509::AID-JMS323>3.0.CO;2-B}}</ref><ref name="PoolAuto97">{{cite journal |title=Automated extraction of pure mass spectra from gas chromatographic/mass spectrometric data |journal=Journal Of Mass Spectrometry |author=Pool, W.G.; deLeeuw, J.W.; vandeGraaf, B. |volume=32 |issue=4 |pages=438–443 |year=1997 |doi=10.1002/(SICI)1096-9888(199704)32:4<438::AID-JMS499>3.0.CO;2-N}}</ref> and Davies<ref name="DaviesTheNew98">{{cite journal |title=The new Automated Mass Spectrometry Deconvolution and Identification System (AMDIS) |journal=Spectrometry Europe |author=Davies, A. |volume=10 |issue=3 |pages=22–26 |year=1998}}</ref> in various ways. Stein<ref name="SteinAnInt99">{{cite journal |title=An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data |journal=Journal Of the American Society for Mass Spectrometry |author=Stein, S.E. |volume=10 |issue=8 |pages=770–781 |year=1999 |doi=10.1016/S1044-0305(99)00047-1}}</ref> published an enhanced deconvolution algorithm that has been implemented in the software AMDIS (Automated Mass Spectral Deconvolution and Identification System).<ref name="AMDIS">{{cite web |url=http://chemdata.nist.gov/dokuwiki/doku.php?id=chemdata:amdis |title=AMDIS |publisher=The National Institute of Standards and Technology}}</ref> AMDIS is available free of charge from the National Institute of Standards and Technology (NIST). Windig et al.<ref name="WindigChemo07">{{cite journal |title=Chemometric analysis of complex hyphenated data: Improvements of the component detection algorithm |journal=Journal of Chromatography A |author=Windig, W.; Smith, W.F. |volume=1158 |issue=1–2 |pages=251–257 |year=2007 |doi=10.1016/j.chroma.2007.03.081 |pmid=17418223}}</ref><ref name="WindigANoise96">{{cite journal |title=A noise and background reduction method for component detection in liquid chromatography/mass spectrometry |journal=Analytical Chemistry |author=Windig, W.; Phalp, J.M.; Payne, A.W. |volume=68 |issue=20 |pages=3602–3606 |year=1996 |doi=10.1021/ac960435y}}</ref> described another approach to enhance chromatographic quality by a deconvolution method called CODA (Component Detection Algorithm). The commercially available software ACD/MS Manager<ref name="ACD/MS">{{cite web |url=http://www.acdlabs.com/ |title=ACD/Labs |publisher=Advanced Chemistry Development, Inc}}</ref> offers an implementation of this approach.
Software has become an integral part of analysis techniques. Especially in the area of gas chromatography/mass spectrometry, automatic samplers enable high throughput analyses. Software assists handling large amounts of data generated by automated and fast operating analytical instruments. Modern computer systems are inexpensive, powerful and allow analysis techniques that could not have been applied in the past. Deconvolution, a chromatographic quality enhancing technique, demonstrates for instance that increasing processor power makes new analysis techniques applicable. The technique of deconvolution has been described by Biller and Biemann<ref name="BillerIdent77">{{cite journal |title=Identification of the components of complex mixtures by GC-MS |journal=Abstracts Of Papers Of The American Chemical Society |author=Biller, J.E.; Herlihy, W.C.; Biemann, K. |volume=173 |issue=MAR20 |pages=23–23 |year=1977 |url=http://pubs.acs.org/doi/abs/10.1021/bk-1977-0054.ch002}}</ref><ref name="BillerRecon74">{{cite journal |title=Reconstructed Mass Spectra, A Novel Approach for the Utilization of Gas Chromatograph—Mass Spectrometer Data |journal=Analytical Letters |author=Biller, J.E.; Biemann, K. |volume=7 |issue=7 |pages=515–528 |year=1974 |doi=10.1080/00032717408058783}}</ref>, Dromey et al.<ref name="FromeyExtract76">{{cite journal |title=Extraction of mass spectra free of background and neighboring component contributions from gas chromatography/mass spectrometry data |journal=Analytical Chemistry |author=Dromey, R.G.; Stefik, M.J.; Rindfleisch, T.C.; Duffield, A.M. |volume=48 |issue=9 |pages=1368–1375 |year=1976 |doi=10.1021/ac50003a027}}</ref>, Colby<ref name="ColbySpect92">{{cite journal |title=Spectral deconvolution for overlapping GC/MS components |journal=Journal of the American Society for Mass Spectrometry |author=Colby, B.N. |volume=3 |issue=5 |pages=558–562 |year=1992 |doi=10.1016/1044-0305(92)85033-G |pmid=24234499}}</ref>, Hindmarch et al.<ref name="HindmarchDecon96">{{cite journal |title=Deconvolution and spectral clean-up of two-component mixtures by factor analysis of gas chromatographic–mass spectrometric data |journal=Analyst |author=Hindmarch, P.; Demir, C.; Brereton, R.G. |volume=121 |issue=8 |pages=993-1001 |year=1996 |doi=10.1039/AN9962100993}}</ref>, Halket et al.<ref name="HalketDecon99">{{cite journal |title=Deconvolution gas chromatography/mass spectrometry of urinary organic acids – potential for pattern recognition and automated identification of metabolic disorders |journal=Rapid Communications In Mass Spectrometry |author=Halket, J.M.; Przyborowska, A.; Stein, S.E. et al. |volume=13 |issue=4 |pages=279–284 |year=1999 |doi=10.1002/(SICI)1097-0231(19990228)13:4<279::AID-RCM478>3.0.CO;2-I |pmid=10097403}}</ref>, Kong et al.<ref name="KongDecon05">{{cite journal |title=Deconvolution of overlapped peaks based on the exponentially modified Gaussian model in comprehensive two-dimensional gas chromatography |journal=Journal of Chromatography A |author=Kong, H.W.; Ye, F.; Lu, X.; Guo, L.; Tian, J.; Xu, G.W. |volume=1086 |issue=1–2 |pages=160–164 |year=2005 |doi=10.1016/j.chroma.2005.05.103 |pmid=16130668}}</ref>, Taylor et al.<ref name="TaylorTheDecon98">{{cite journal |title=The deconvolution of pyrolysis mass spectra using genetic programming: Application to the identification of some ''Eubacterium'' species |journal=FEMS Microbiology Letters |author=Taylor, J.; Goodacre, R.; Wade, W.G. |volume=160 |issue=2 |pages=237–246 |year=1998 |doi=10.1111/j.1574-6968.1998.tb12917.x |pmid=9532743}}</ref>, Pool et al.<ref name="PoolBack96">{{cite journal |title=Backfolding applied to differential gas chromatography/mass spectrometry as a mathematical enhancement of chromatographic resolution |journal=Journal Of Mass Spectrometry |author=Pool, W.G.; deLeeuw, J.W.; vandeGraaf, B. |volume=31 |issue=5 |pages=509–516 |year=1996 |doi=10.1002/(SICI)1096-9888(199605)31:5<509::AID-JMS323>3.0.CO;2-B}}</ref><ref name="PoolAuto97">{{cite journal |title=Automated extraction of pure mass spectra from gas chromatographic/mass spectrometric data |journal=Journal Of Mass Spectrometry |author=Pool, W.G.; deLeeuw, J.W.; vandeGraaf, B. |volume=32 |issue=4 |pages=438–443 |year=1997 |doi=10.1002/(SICI)1096-9888(199704)32:4<438::AID-JMS499>3.0.CO;2-N}}</ref> and Davies<ref name="DaviesTheNew98">{{cite journal |title=The new Automated Mass Spectrometry Deconvolution and Identification System (AMDIS) |journal=Spectrometry Europe |author=Davies, A. |volume=10 |issue=3 |pages=22–26 |year=1998}}</ref> in various ways. Stein<ref name="SteinAnInt99">{{cite journal |title=An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data |journal=Journal Of the American Society for Mass Spectrometry |author=Stein, S.E. |volume=10 |issue=8 |pages=770–781 |year=1999 |doi=10.1016/S1044-0305(99)00047-1}}</ref> published an enhanced deconvolution algorithm that has been implemented in the software AMDIS (Automated Mass Spectral Deconvolution and Identification System).<ref name="AMDIS">{{cite web |url=http://chemdata.nist.gov/dokuwiki/doku.php?id=chemdata:amdis |title=AMDIS |publisher=The National Institute of Standards and Technology}}</ref> AMDIS is available free of charge from the National Institute of Standards and Technology (NIST). Windig et al.<ref name="WindigChemo07">{{cite journal |title=Chemometric analysis of complex hyphenated data: Improvements of the component detection algorithm |journal=Journal of Chromatography A |author=Windig, W.; Smith, W.F. |volume=1158 |issue=1–2 |pages=251–257 |year=2007 |doi=10.1016/j.chroma.2007.03.081 |pmid=17418223}}</ref><ref name="WindigANoise96">{{cite journal |title=A noise and background reduction method for component detection in liquid chromatography/mass spectrometry |journal=Analytical Chemistry |author=Windig, W.; Phalp, J.M.; Payne, A.W. |volume=68 |issue=20 |pages=3602–3606 |year=1996 |doi=10.1021/ac960435y}}</ref> described another approach to enhance chromatographic quality by a deconvolution method called CODA (Component Detection Algorithm). The commercially available software ACD/MS Manager<ref name="ACD/MS">{{cite web |url=http://www.acdlabs.com/ |title=ACD/Labs |publisher=Advanced Chemistry Development, Inc}}</ref> offers an implementation of this approach.
Increasing computational power enables new applications, but there is still a lack of interoperability. Instrument vendors, such as [[Agilent Technologies, Inc.|Agilent Technologies]], [[Shimadzu Corporation|Shimadzu]], [[Thermo Scientific|Thermo Fisher Scientific]] and [[Waters Corporation]] have created their own software and data format. Usually, the mass spectral data formats are binary and can only be accessed by the instrument vendors' proprietary software. Some commercial tools exist to convert the mass spectral data files into other formats, such as MASS Transit from PALISADE Corporation.<ref name="PALISADE">{{cite web |url=http://www.palisade.com/ |title=PALISADE |publisher=Palisade Corporation}}</ref> To avoid these limitations, some efforts have been made to design and implement interoperable data formats and software libraries as for example NetCDF<ref name="NetCDF">{{cite web |url=http://www.unidata.ucar.edu/software/netcdf/ |title=Network Common Data Form (NetCDF) |publisher=University Corporation for Atmospheric Research}}</ref> or mzXML.<ref name="PedrioliACommon04">{{cite journal |title=A common open representation of mass spectrometry data and its application to proteomics research |journal=Nature Biotechnology |author=Pedrioli, P.G.A.; Eng, J.K.; Hubley, R. |volume=22 |issue=11 |pages=1459–1466 |year=2004 |doi=10.1038/nbt1031 |pmid=15529173}}</ref><ref name="FalknerProt07">{{cite journal |title=ProteomeCommons.org IO Framework: Reading and writing multiple proteomics data formats |journal=Bioinformatics |author=Falkner, J.A.; Falkner, J.W.; Andrews, P.C. |volume=23 |issue=2 |pages=262–263 |year=2007 |doi=10.1093/bioinformatics/btl573 |pmid=17121776}}</ref> But even if it is possible to convert the data files to other formats, there are drawbacks in data processing as each software implements specific functions, has its own graphical user interface and is in most cases commercially available only, as for example the applicable software of ChemStation, Xcalibur or MassLynx. Hence, the users are forced to become familiar with different software systems, user interfaces and methods. Moreover, the software tools primarily target only specific operating systems, such as Microsoft Windows and Mac OSX. The number of software applications that are independent of the operating system and can also be run under Unix or Linux is limited. Linux systems are open source, available at no cost and their usage increases in scientific research (see Scientific Linux<ref name="SciLin">{{cite web |url=https://en.wikipedia.org/wiki/Scientific_Linux |title=Scientific Linux |work=Wikipedia |publisher=Wikimedia Foundation, Inc}}</ref>), as well as in the public sector.<ref name="Wienux">{{cite web |url=https://en.wikipedia.org/wiki/Wienux |title=Wienux |work=Wikipedia |publisher=Wikimedia Foundation, Inc}}</ref><ref name="LiMux">{{cite web |url=http://www.muenchen.de/rathaus/Stadtverwaltung/Direktorium/LiMux.html |title=Das Projekt LiMux |publisher=Portal München Betriebs-GmbH & Co. KG}}</ref> Software applications, such as AMDIS, have been published to be used free of charge, but their source code is not disposable. Thus, it is not possible to evaluate the algorithms implemented in the software. Especially in the case of scientific research, it is not possible to figure them out and to extend them. Even if algorithms are described in published papers<ref name="BillerRecon74" /><ref name="ColbySpect92" /><ref name="PoolBack96" /><ref name="SteinAnInt99" /><ref name="AlfassiOnThe04">{{cite journal |title=On the normalization of a mass spectrum for comparison of two spectra |journal=Journal of the American Society for Mass Spectrometry |author=Alfassi, Z.B. |volume=15 |issue=3 |pages=385-387 |year=2004 |doi=10.1016/j.jasms.2003.11.008 |pmid=14998540}}</ref>, it is often impossible to validate them manually due to the complexity of chromatographic data. Other applications like ChemStation, Xcalibur, and ACD/MS Manager are proprietary and closed source. They are only commercially available. There is no means of revealing the correctness of their utilized algorithms. Efforts have been made to solve the problems of missing interoperability and restricted access to source codes and algorithms.<ref name="SpjuthBio07">{{cite journal |title=Bioclipse: An open source workbench for chemo- and bioinformatics |journal=BMC Bioinformatics |author=Spjuth, O.; Helmus, T.; Willighagen, E.L. et al. |volume=8 |pages=59 |year=2007 |doi=10.1186/1471-2105-8-59 |pmid=17316423 |pmc=PMC1808478}}</ref> Bioclipse is a sophisticated project that is open source and is focused with its algorithms on metabolism analysis and gene sequencing. Its techniques are state-of-the-art. Some other projects are mMass<ref name="mMassArch">{{cite web |url=http://mmass.biographics.cz/ |archiveurl=https://web.archive.org/web/20090827071924/http://mmass.biographics.cz/ |title=mMass - Open Source Mass Spectrometry Tool |publisher=Martin Strohalm |archivedate=27 August 2009}}</ref>, COMSPARI<ref name="COMSPARI">{{cite web |url=http://www.biomechanic.org/comspari/ |title=The COMSPARI Homepage |publisher=J. Katz and J. Hau}}</ref> and fityk<ref name="fitykArch">{{cite web |url=http://www.unipress.waw.pl/fityk/ |archiveurl=https://web.archive.org/web/20100304192315/http://www.unipress.waw.pl/fityk |title=Fityk home |publisher=Institute of High Pressure Physics of the Polish Academy of Sciences |archivedate=04 March 2010}}</ref>, but they do have some restrictions regarding their interoperability and extensibility. BioSunMS<ref name="CaoBio09">{{cite journal |title=BioSunMS: A plug-in-based software for the management of patients information and the analysis of peptide profiles from mass spectrometry |journal=BMC Medical Informatics and Decision Making |author=Cao, Y.; Wang, N.; Ying, X.M. et al. |volume=9 |pages=13 |year=2009 |doi=10.1186/1472-6947-9-13 |pmid=17316423 |pmc=PMC1808478}}</ref> is a tool to read TOF (Time of Flight) mass spectral data files, but it is not able to read instrument vendors' native data files. The Chemistry Development Kit (CDK)<ref name="SteinbeckTheChem03">{{cite journal |title=The Chemistry Development Kit (CDK): An open-source Java library for Chemo- and Bioinformatics |journal=Journal of Chemical Information and Computer Sciences |author=Steinbeck, C.; Han, Y.Q.; Kuhn, S. et al. |volume=43 |issue=2 |pages=493–500 |year=2003 |pmid=12653513}}</ref> implements convenient features to edit chemical data and structures, but it has no appropriate user interface. The open source tool OpenMS<ref name="SturmOpenMS08">{{cite journal |title=OpenMS – An open-source software framework for mass spectrometry |journal=BMC Bioinformatics |author=Sturm, M.; Bertsch, A.; Gropl, C. et al. |volume=9 |pages=163 |year=2008 |doi=10.1186/1471-2105-9-163 |pmid=18366760 |pmc=PMC2311306}}</ref> aims to edit mass spectrometric data, but it is not completely platform independent, as it is written in C++ programming language.


==References==
==References==

Revision as of 22:20, 25 March 2016

Full article title OpenChrom: A cross-platform open source software for the mass spectrometric analysis of chromatographic data
Journal BMC Bioinformatics
Author(s) Wenig, Philip; Odermatt, Juergen
Author affiliation(s) University of Hamburg
Primary contact Email: philip.wenig@gmx.net
Year published 2010
Volume and issue 11
Page(s) 405
DOI [1]
ISSN 1471-2105
Distribution license Creative Commons Attribution 2.0 Generic
Website http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-405
Download http://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/1471-2105-11-405 (PDF)
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Abstract

Background

Today, 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.

Results

This 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.

Conclusions

OpenChrom is a chromatography 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.

Background

Software has become an integral part of analysis techniques. Especially in the area of gas chromatography/mass spectrometry, automatic samplers enable high throughput analyses. Software assists handling large amounts of data generated by automated and fast operating analytical instruments. Modern computer systems are inexpensive, powerful and allow analysis techniques that could not have been applied in the past. Deconvolution, a chromatographic quality enhancing technique, demonstrates for instance that increasing processor power makes new analysis techniques applicable. The technique of deconvolution has been described by Biller and Biemann[1][2], Dromey et al.[3], Colby[4], Hindmarch et al.[5], Halket et al.[6], Kong et al.[7], Taylor et al.[8], Pool et al.[9][10] and Davies[11] in various ways. Stein[12] published an enhanced deconvolution algorithm that has been implemented in the software AMDIS (Automated Mass Spectral Deconvolution and Identification System).[13] AMDIS is available free of charge from the National Institute of Standards and Technology (NIST). Windig et al.[14][15] described another approach to enhance chromatographic quality by a deconvolution method called CODA (Component Detection Algorithm). The commercially available software ACD/MS Manager[16] offers an implementation of this approach.

Increasing computational power enables new applications, but there is still a lack of interoperability. Instrument vendors, such as Agilent Technologies, Shimadzu, Thermo Fisher Scientific and Waters Corporation have created their own software and data format. Usually, the mass spectral data formats are binary and can only be accessed by the instrument vendors' proprietary software. Some commercial tools exist to convert the mass spectral data files into other formats, such as MASS Transit from PALISADE Corporation.[17] To avoid these limitations, some efforts have been made to design and implement interoperable data formats and software libraries as for example NetCDF[18] or mzXML.[19][20] But even if it is possible to convert the data files to other formats, there are drawbacks in data processing as each software implements specific functions, has its own graphical user interface and is in most cases commercially available only, as for example the applicable software of ChemStation, Xcalibur or MassLynx. Hence, the users are forced to become familiar with different software systems, user interfaces and methods. Moreover, the software tools primarily target only specific operating systems, such as Microsoft Windows and Mac OSX. The number of software applications that are independent of the operating system and can also be run under Unix or Linux is limited. Linux systems are open source, available at no cost and their usage increases in scientific research (see Scientific Linux[21]), as well as in the public sector.[22][23] Software applications, such as AMDIS, have been published to be used free of charge, but their source code is not disposable. Thus, it is not possible to evaluate the algorithms implemented in the software. Especially in the case of scientific research, it is not possible to figure them out and to extend them. Even if algorithms are described in published papers[2][4][9][12][24], it is often impossible to validate them manually due to the complexity of chromatographic data. Other applications like ChemStation, Xcalibur, and ACD/MS Manager are proprietary and closed source. They are only commercially available. There is no means of revealing the correctness of their utilized algorithms. Efforts have been made to solve the problems of missing interoperability and restricted access to source codes and algorithms.[25] Bioclipse is a sophisticated project that is open source and is focused with its algorithms on metabolism analysis and gene sequencing. Its techniques are state-of-the-art. Some other projects are mMass[26], COMSPARI[27] and fityk[28], but they do have some restrictions regarding their interoperability and extensibility. BioSunMS[29] is a tool to read TOF (Time of Flight) mass spectral data files, but it is not able to read instrument vendors' native data files. The Chemistry Development Kit (CDK)[30] implements convenient features to edit chemical data and structures, but it has no appropriate user interface. The open source tool OpenMS[31] aims to edit mass spectrometric data, but it is not completely platform independent, as it is written in C++ programming language.

References

  1. ↑ Biller, J.E.; Herlihy, W.C.; Biemann, K. (1977). "Identification of the components of complex mixtures by GC-MS". Abstracts Of Papers Of The American Chemical Society 173 (MAR20): 23–23. http://pubs.acs.org/doi/abs/10.1021/bk-1977-0054.ch002. 
  2. ↑ 2.0 2.1 Biller, J.E.; Biemann, K. (1974). "Reconstructed Mass Spectra, A Novel Approach for the Utilization of Gas Chromatograph—Mass Spectrometer Data". Analytical Letters 7 (7): 515–528. doi:10.1080/00032717408058783. 
  3. ↑ Dromey, R.G.; Stefik, M.J.; Rindfleisch, T.C.; Duffield, A.M. (1976). "Extraction of mass spectra free of background and neighboring component contributions from gas chromatography/mass spectrometry data". Analytical Chemistry 48 (9): 1368–1375. doi:10.1021/ac50003a027. 
  4. ↑ 4.0 4.1 Colby, B.N. (1992). "Spectral deconvolution for overlapping GC/MS components". Journal of the American Society for Mass Spectrometry 3 (5): 558–562. doi:10.1016/1044-0305(92)85033-G. PMID 24234499. 
  5. ↑ Hindmarch, P.; Demir, C.; Brereton, R.G. (1996). "Deconvolution and spectral clean-up of two-component mixtures by factor analysis of gas chromatographic–mass spectrometric data". Analyst 121 (8): 993-1001. doi:10.1039/AN9962100993. 
  6. ↑ Halket, J.M.; Przyborowska, A.; Stein, S.E. et al. (1999). "Deconvolution gas chromatography/mass spectrometry of urinary organic acids – potential for pattern recognition and automated identification of metabolic disorders". Rapid Communications In Mass Spectrometry 13 (4): 279–284. doi:10.1002/(SICI)1097-0231(19990228)13:4<279::AID-RCM478>3.0.CO;2-I. PMID 10097403. 
  7. ↑ Kong, H.W.; Ye, F.; Lu, X.; Guo, L.; Tian, J.; Xu, G.W. (2005). "Deconvolution of overlapped peaks based on the exponentially modified Gaussian model in comprehensive two-dimensional gas chromatography". Journal of Chromatography A 1086 (1–2): 160–164. doi:10.1016/j.chroma.2005.05.103. PMID 16130668. 
  8. ↑ Taylor, J.; Goodacre, R.; Wade, W.G. (1998). "The deconvolution of pyrolysis mass spectra using genetic programming: Application to the identification of some Eubacterium species". FEMS Microbiology Letters 160 (2): 237–246. doi:10.1111/j.1574-6968.1998.tb12917.x. PMID 9532743. 
  9. ↑ 9.0 9.1 Pool, W.G.; deLeeuw, J.W.; vandeGraaf, B. (1996). "Backfolding applied to differential gas chromatography/mass spectrometry as a mathematical enhancement of chromatographic resolution". Journal Of Mass Spectrometry 31 (5): 509–516. doi:10.1002/(SICI)1096-9888(199605)31:5<509::AID-JMS323>3.0.CO;2-B. 
  10. ↑ Pool, W.G.; deLeeuw, J.W.; vandeGraaf, B. (1997). "Automated extraction of pure mass spectra from gas chromatographic/mass spectrometric data". Journal Of Mass Spectrometry 32 (4): 438–443. doi:10.1002/(SICI)1096-9888(199704)32:4<438::AID-JMS499>3.0.CO;2-N. 
  11. ↑ Davies, A. (1998). "The new Automated Mass Spectrometry Deconvolution and Identification System (AMDIS)". Spectrometry Europe 10 (3): 22–26. 
  12. ↑ 12.0 12.1 Stein, S.E. (1999). "An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data". Journal Of the American Society for Mass Spectrometry 10 (8): 770–781. doi:10.1016/S1044-0305(99)00047-1. 
  13. ↑ "AMDIS". The National Institute of Standards and Technology. http://chemdata.nist.gov/dokuwiki/doku.php?id=chemdata:amdis. 
  14. ↑ Windig, W.; Smith, W.F. (2007). "Chemometric analysis of complex hyphenated data: Improvements of the component detection algorithm". Journal of Chromatography A 1158 (1–2): 251–257. doi:10.1016/j.chroma.2007.03.081. PMID 17418223. 
  15. ↑ Windig, W.; Phalp, J.M.; Payne, A.W. (1996). "A noise and background reduction method for component detection in liquid chromatography/mass spectrometry". Analytical Chemistry 68 (20): 3602–3606. doi:10.1021/ac960435y. 
  16. ↑ "ACD/Labs". Advanced Chemistry Development, Inc. http://www.acdlabs.com/. 
  17. ↑ "PALISADE". Palisade Corporation. http://www.palisade.com/. 
  18. ↑ "Network Common Data Form (NetCDF)". University Corporation for Atmospheric Research. http://www.unidata.ucar.edu/software/netcdf/. 
  19. ↑ Pedrioli, P.G.A.; Eng, J.K.; Hubley, R. (2004). "A common open representation of mass spectrometry data and its application to proteomics research". Nature Biotechnology 22 (11): 1459–1466. doi:10.1038/nbt1031. PMID 15529173. 
  20. ↑ Falkner, J.A.; Falkner, J.W.; Andrews, P.C. (2007). "ProteomeCommons.org IO Framework: Reading and writing multiple proteomics data formats". Bioinformatics 23 (2): 262–263. doi:10.1093/bioinformatics/btl573. PMID 17121776. 
  21. ↑ "Scientific Linux". Wikipedia. Wikimedia Foundation, Inc. https://en.wikipedia.org/wiki/Scientific_Linux. 
  22. ↑ "Wienux". Wikipedia. Wikimedia Foundation, Inc. https://en.wikipedia.org/wiki/Wienux. 
  23. ↑ "Das Projekt LiMux". Portal München Betriebs-GmbH & Co. KG. http://www.muenchen.de/rathaus/Stadtverwaltung/Direktorium/LiMux.html. 
  24. ↑ Alfassi, Z.B. (2004). "On the normalization of a mass spectrum for comparison of two spectra". Journal of the American Society for Mass Spectrometry 15 (3): 385-387. doi:10.1016/j.jasms.2003.11.008. PMID 14998540. 
  25. ↑ Spjuth, O.; Helmus, T.; Willighagen, E.L. et al. (2007). "Bioclipse: An open source workbench for chemo- and bioinformatics". BMC Bioinformatics 8: 59. doi:10.1186/1471-2105-8-59. PMC PMC1808478. PMID 17316423. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1808478. 
  26. ↑ "mMass - Open Source Mass Spectrometry Tool". Martin Strohalm. Archived from the original on 27 August 2009. https://web.archive.org/web/20090827071924/http://mmass.biographics.cz/. 
  27. ↑ "The COMSPARI Homepage". J. Katz and J. Hau. http://www.biomechanic.org/comspari/. 
  28. ↑ "Fityk home". Institute of High Pressure Physics of the Polish Academy of Sciences. Archived from the original on 04 March 2010. https://web.archive.org/web/20100304192315/http://www.unipress.waw.pl/fityk. 
  29. ↑ Cao, Y.; Wang, N.; Ying, X.M. et al. (2009). "BioSunMS: A plug-in-based software for the management of patients information and the analysis of peptide profiles from mass spectrometry". BMC Medical Informatics and Decision Making 9: 13. doi:10.1186/1472-6947-9-13. PMC PMC1808478. PMID 17316423. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1808478. 
  30. ↑ Steinbeck, C.; Han, Y.Q.; Kuhn, S. et al. (2003). "The Chemistry Development Kit (CDK): An open-source Java library for Chemo- and Bioinformatics". Journal of Chemical Information and Computer Sciences 43 (2): 493–500. PMID 12653513. 
  31. ↑ Sturm, M.; Bertsch, A.; Gropl, C. et al. (2008). "OpenMS – An open-source software framework for mass spectrometry". BMC Bioinformatics 9: 163. doi:10.1186/1471-2105-9-163. PMC PMC2311306. PMID 18366760. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2311306. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. In the "Conclusion" section of the abstract, "software" was changed to "chromatography software" to encourage internal linking to the CDMS entry on the wiki.

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