OpenChrom

Last updated
OpenChrom
Developer(s) Lablicate & Scientific community [1]
Stable release
1.5.0 (rolling)
Written inJava [2]
Operating system Cross-platform
Type Chemoinformatics/Bioinformatics
License EPL, Third-party libraries under various OSI compatible licenses [3]
Website https://www.openchrom.net

OpenChrom is an open source software for the analysis and visualization of mass spectrometric and chromatographic data. [4] Its focus is to handle native data files from several mass spectrometry systems (e.g. GC/MS, LC/MS, Py-GC/MS, HPLC-MS), vendors like Agilent Technologies, Varian, Shimadzu, Thermo Fisher, PerkinElmer and others. But also data formats from other detector types are supported recently.

Contents

OpenChrom supports only the analysis and representation of chromatographic and mass spectrometric data. It has no capabilities for data acquisition or control of vendor hardware. OpenChrom is built on the Eclipse Rich Client Platform (RCP), hence it is available for various operating systems, e.g. Microsoft Windows, macOS and Linux. It is distributed under the Eclipse Public License 1.0 (EPL). Third-party libraries are separated into single bundles and are released under various OSI compatible licenses.

History

ChemClipse version 0.7.0 ChemClipse-0-7-0.png
ChemClipse version 0.7.0

OpenChrom was developed by Philip Wenig as part of his PhD thesis at the University of Hamburg, Germany. [5] The focus of the thesis was to apply pattern recognition techniques on datasets recorded by analytical pyrolysis coupled with chromatography and mass spectrometry (Py-GC/MS). [6] [7]

OpenChrom won the Thomas Krenn Open Source Award 2010 [8] as well as the Eclipse Community Award 2011. [9] The developers are also founding members of the Eclipse Science Working Group. [10] After successful commercialization of contract development and services around the OpenChrom project, vendor Lablicate reinforced the commitment to Free/Libre/Open-Source Software with the release of ChemClipse in October 2016, which serves as the base for all OpenChrom products. [11]

Supported data formats

Each system vendor stores the recorded analysis data in its own proprietary format. That makes it difficult to compare data sets from different systems and vendors. Furthermore, it's a big drawback for interlaboratory tests. The aim of OpenChrom is to support a wide range of different mass spectrometry data formats natively. [12] OpenChrom takes care that the raw data files can't be modified according to the good laboratory practice. To help scientists OpenChrom supports several open formats to import and export the analysis results. In addition, OpenChrom offers its own open source format (*.ocb) that makes it possible to save the edited chromatogram as well as the peaks and identification results.

Mass selective detector

Flame ionization detector

Diode-array detection

Fourier-transform infrared spectroscopy

Near-infrared spectroscopy

Other formats

Major features

OpenChrom offers a variety of features to analyze chromatographic data:

Releases

The software was first released in 2010. Each release is named after a famous scientist.

CodenameEponymDateVersion
Thomson Joseph John Thomson April 2010Old version, no longer maintained: 0.1.0
Goldstein Eugen Goldstein May 2010Old version, no longer maintained: 0.2.0
Wien Wilhelm Wien October 2010Old version, no longer maintained: 0.3.0
Tswett Mikhail Semyonovich Tswett April 2011Old version, no longer maintained: 0.4.0
Martin Archer John Porter Martin October 2011Old version, no longer maintained: 0.5.0
Synge Richard L. M. Synge April 2012Old version, no longer maintained: 0.6.0
Nernst Walther Nernst October 2012Old version, no longer maintained: 0.7.0
Dempster Arthur Jeffrey Dempster July 2013Old version, no longer maintained: 0.8.0
Mattauch Josef Mattauch July 2014Old version, no longer maintained: 0.9.0
Aston Francis William Aston July 2015Old version, no longer maintained: 1.0.0
Diels Otto Diels July 2016Old version, no longer maintained: 1.1.0
Alder Kurt Alder August 2017Old version, no longer maintained: 1.2.0
Dalton John Dalton August 2018Old version, no longer maintained: 1.3.0
Lawrence Ernest Lawrence August 2019Old version, no longer maintained: 1.4.0
McLafferty Fred McLafferty March 2022Current stable version:1.5.0 [note 1]
Legend:
Old version
Older version, still maintained
Latest version
Latest preview version
Future release
  1. Rolling Release from here. Only the timestamp changes.

Related Research Articles

In chemical analysis, chromatography is a laboratory technique for the separation of a mixture into its components. The mixture is dissolved in a fluid solvent called the mobile phase, which carries it through a system on which a material called the stationary phase is fixed. Because the different constituents of the mixture tend to have different affinities for the stationary phase and are retained for different lengths of time depending on their interactions with its surface sites, the constituents travel at different apparent velocities in the mobile fluid, causing them to separate. The separation is based on the differential partitioning between the mobile and the stationary phases. Subtle differences in a compound's partition coefficient result in differential retention on the stationary phase and thus affect the separation.

<span class="mw-page-title-main">High-performance liquid chromatography</span> Technique in analytical chemistry

High-performance liquid chromatography (HPLC), formerly referred to as high-pressure liquid chromatography, is a technique in analytical chemistry used to separate, identify, and quantify specific components in mixtures. The mixtures can originate from food, chemicals, pharmaceuticals, biological, environmental and agriculture, etc., which have been dissolved into liquid solutions.

Gel permeation chromatography (GPC) is a type of size-exclusion chromatography (SEC), that separates high molecular weight or colloidal analytes on the basis of size or diameter, typically in organic solvents. The technique is often used for the analysis of polymers. As a technique, SEC was first developed in 1955 by Lathe and Ruthven. The term gel permeation chromatography can be traced back to J.C. Moore of the Dow Chemical Company who investigated the technique in 1964. The proprietary column technology was licensed to Waters Corporation, who subsequently commercialized this technology in 1964. GPC systems and consumables are now also available from a number of manufacturers. It is often necessary to separate polymers, both to analyze them as well as to purify the desired product.

<span class="mw-page-title-main">Gas chromatography</span> Type of chromatography

Gas chromatography (GC) is a common type of chromatography used in analytical chemistry for separating and analyzing compounds that can be vaporized without decomposition. Typical uses of GC include testing the purity of a particular substance, or separating the different components of a mixture. In preparative chromatography, GC can be used to prepare pure compounds from a mixture.

<span class="mw-page-title-main">Gas chromatography–mass spectrometry</span> Analytical method

Gas chromatography–mass spectrometry (GC–MS) is an analytical method that combines the features of gas-chromatography and mass spectrometry to identify different substances within a test sample. Applications of GC–MS include drug detection, fire investigation, environmental analysis, explosives investigation, food and flavor analysis, and identification of unknown samples, including that of material samples obtained from planet Mars during probe missions as early as the 1970s. GC–MS can also be used in airport security to detect substances in luggage or on human beings. Additionally, it can identify trace elements in materials that were previously thought to have disintegrated beyond identification. Like liquid chromatography–mass spectrometry, it allows analysis and detection even of tiny amounts of a substance.

<span class="mw-page-title-main">Metabolomics</span> Scientific study of chemical processes involving metabolites

Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.

Mass spectrometry is a scientific technique for measuring the mass-to-charge ratio of ions. It is often coupled to chromatographic techniques such as gas- or liquid chromatography and has found widespread adoption in the fields of analytical chemistry and biochemistry where it can be used to identify and characterize small molecules and proteins (proteomics). The large volume of data produced in a typical mass spectrometry experiment requires that computers be used for data storage and processing. Over the years, different manufacturers of mass spectrometers have developed various proprietary data formats for handling such data which makes it difficult for academic scientists to directly manipulate their data. To address this limitation, several open, XML-based data formats have recently been developed by the Trans-Proteomic Pipeline at the Institute for Systems Biology to facilitate data manipulation and innovation in the public sector. These data formats are described here.

Mascot is a software search engine that uses mass spectrometry data to identify proteins from peptide sequence databases. Mascot is widely used by research facilities around the world. Mascot uses a probabilistic scoring algorithm for protein identification that was adapted from the MOWSE algorithm. Mascot is freely available to use on the website of Matrix Science. A license is required for in-house use where more features can be incorporated.

Chromatography software is called also Chromatography Data System. It is located in the data station of the modern liquid, gas or supercritical fluid chromatographic systems. This is a dedicated software connected to an hardware interface within the chromatographic system, which serves as a central hub for collecting, analyzing, and managing the data generated during the chromatographic analysis.

<span class="mw-page-title-main">Two-dimensional chromatography</span>

Two-dimensional chromatography is a type of chromatographic technique in which the injected sample is separated by passing through two different separation stages. Two different chromatographic columns are connected in sequence, and the effluent from the first system is transferred onto the second column. Typically the second column has a different separation mechanism, so that bands that are poorly resolved from the first column may be completely separated in the second column. Alternately, the two columns might run at different temperatures. During the second stage of separation the rate at which the separation occurs must be faster than the first stage, since there is still only a single detector. The plane surface is amenable to sequential development in two directions using two different solvents.

NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. The project homepage is hosted by the Unidata program at the University Corporation for Atmospheric Research (UCAR). They are also the chief source of netCDF software, standards development, updates, etc. The format is an open standard. NetCDF Classic and 64-bit Offset Format are an international standard of the Open Geospatial Consortium.

OpenMS is an open-source project for data analysis and processing in mass spectrometry and is released under the 3-clause BSD licence. It supports most common operating systems including Microsoft Windows, MacOS and Linux.

Pittcon Editors’ Awards honoured the best new products on show at the Pittsburgh Conference on Analytical Chemistry and Applied Spectroscopy, or Pittcon, for 20 years from 1996 having been established by Dr Gordon Wilkinson, managing editor of Analytical Instrument Industry Report. On 8 March 2015, the event returned to the Morial Convention Center in New Orleans and this was the last occasion when the awards were presented.

A chromatography detector is a device that detects and quantifies separated compounds as they elute from the chromatographic column. These detectors are integral to various chromatographic techniques, such as gas chromatography, liquid chromatography, and high-performance liquid chromatography, and supercritical fluid chromatography among others. The main function of a chromatography detector is to translate the physical or chemical properties of the analyte molecules into measurable signal, typically electrical signal, that can be displayed as a function of time in a graphical presentation, called a chromatograms. Chromatograms can provide valuable information about the composition and concentration of the components in the sample.

Comprehensive two-dimensional gas chromatography, or GC×GC, is a multidimensional gas chromatography technique that was originally described in 1984 by J. Calvin Giddings and first successfully implemented in 1991 by John Phillips and his student Zaiyou Liu.

The component detection algorithm (CODA) is a name for a type of LC-MS and chemometrics software algorithm focused on detecting peaks in noisy chromatograms (TIC) often obtained using the electrospray ionization technique.

Gas chromatography–vacuum ultraviolet spectroscopy (GC-VUV) is a universal detection technique for gas chromatography. VUV detection provides both qualitative and quantitative spectral information for most gas phase compounds.

Skyline is an open source software for targeted proteomics and metabolomics data analysis. It runs on Microsoft Windows and supports the raw data formats from multiple mass spectrometric vendors. It contains a graphical user interface to display chromatographic data for individual peptide or small molecule analytes.

Within the environmental sciences, screening broadly refers to a set of analytical techniques used to monitor levels of potentially hazardous organic compounds in the environment, particularly in tandem with mass spectrometry techniques. Such screening techniques are typically classified as either targeted, where compounds of interest are chosen before the analysis begins, or non-targeted, where compounds of interest are chosen at a later stage of the analysis. These two techniques can be organized into at least three approaches: target screening, using reference standards that are analogous to the target compound; suspect screening, which uses a library of cataloged data such as exact mass, isotope patterns, and chromatographic retention times in lieu of reference standards; and non-target screening, using no pre-existing knowledge for comparison before analysis. As such, target screening is most useful when monitoring the presence of specific organic compounds—particularly for regulatory purposes—which requires higher selectivity and sensitivity. When the number of detected compounds and associated metabolites needs to be maximized for discovering new or emerging environmental trends or biomarkers for disease, a more non-targeted approach has traditionally been used. However, the rapid improvement of mass spectrometers into more high-resolution forms, with increased sensitivity, has made suspect and non-target screening more attractive, either as stand-alone approaches or in conjunction with more targeted methods.

Gas chromatography-olfactometry (GC-O) is a technique that integrates the separation of volatile compounds using a gas chromatograph with the detection of odour using an olfactometer. It was first invented and applied in 1964 by Fuller and co-workers. While GC separates volatile compounds from an extract, human olfaction detects the odour activity of each eluting compound. In this olfactometric detection, a human assessor may qualitatively determine whether a compound has odour activity or describe the odour perceived, or quantitatively evaluate the intensity of the odour or the duration of the odour activity. The olfactometric detection of compounds allows the assessment of the relationship between a quantified substance and the human perception of its odour, without instrumental detection limits present in other kinds of detectors. Compound identification still requires use of other detectors, such as mass spectrometry, with analytical standards.

References

  1. OpenChrom Contributors, Black Duck OpenHub
  2. The OpenChrom Open Source Project on Open Hub
  3. Eclipse Marketplace: OpenChrom
  4. OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data, Philip Wenig, Juergen Odermatt, BMC Bioinformatics ; 2010; doi : 10.1186/1471-2105-11-405
  5. Softwarebasierte Verfahren zur datenbankgestützten Identifizierung organischer Substanzen mittels analytischer Pyrolyse gekoppelt mit Gaschromatographie/Massenspektrometrie (Py-GC/MS), Philip Wenig, Dissertation; 2012; DNB-IDN   1027167683
  6. Post-optimization of Py-GC/MS data: A case study using a new digital chemical noise reduction filter (NOISERA) to enhance the data quality utilizing OpenChrom mass spectrometric software, Philip Wenig, Journal of Analytical and Applied Pyrolysis ; 2011; doi : 10.1016/j.jaap.2011.05.013
  7. Characterizing odorous emissions using new software for identifying peaks in chemometric models of gas chromatography – mass spectrometry datasets, K.R. Murphy, P. Wenig, G. Parcsi, T. Skov, R.M. Stuetz, Chemometrics and Intelligent Laboratory Systems ; 2012; doi : 10.1016/j.chemolab.2012.07.006
  8. Werner Fischer: Winner Thomas Krenn Open Source Award 2010
  9. Eclipse Foundation: Eclipse Community Awards Winners Announced, Santa Clara, CA - March 21, 2011
  10. Diana Kupfer: Insight into the Eclipse Science Working Group, June 11, 2014
  11. Philip Wenig: ChemClipse 0.7.0 released, October 2, 2016
  12. Dąbrowski, Łukasz (2015-08-07). "Review of free data processing software for chromatography". Mediterranean Journal of Chemistry. 4 (4): 193–200. doi: 10.13171/mjc.4.4.2015.15.09.16.35/dabrowski .