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OpenMS - an open-source software framework for mass spectrometry.

Sturm M, Bertsch A, Gröpl C, Hildebrandt A, Hussong R, Lange E, Pfeifer N, Schulz-Trieglaff O, Zerck A, Reinert K, Kohlbacher O - BMC Bioinformatics (2008)

Bottom Line: Although software tools for many data analysis tasks are available today, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow.OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis.This has already been demonstrated in several studies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Bioinformatics, Eberhard Karls University Tübingen, Sand 14, 72076 Tübingen, Germany. sturm@informatik.uni-tuebingen.de

ABSTRACT

Background: Mass spectrometry is an essential analytical technique for high-throughput analysis in proteomics and metabolomics. The development of new separation techniques, precise mass analyzers and experimental protocols is a very active field of research. This leads to more complex experimental setups yielding ever increasing amounts of data. Consequently, analysis of the data is currently often the bottleneck for experimental studies. Although software tools for many data analysis tasks are available today, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow.

Results: We present OpenMS, a software framework for rapid application development in mass spectrometry. OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis. This has already been demonstrated in several studies.

Conclusion: OpenMS is available under the Lesser GNU Public License (LGPL) from the project website at http://www.openms.de.

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Related in: MedlinePlus

Map alignment example. Left: Two feature maps with varying retention time and mass-to-charge dimensions. Right: The features of the second feature maps were transformed onto the coordinate system of the first feature map.
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Figure 6: Map alignment example. Left: Two feature maps with varying retention time and mass-to-charge dimensions. Right: The features of the second feature maps were transformed onto the coordinate system of the first feature map.

Mentions: OpenMS offers algorithms to align multiple experiments and to match the corresponding ion species across many samples. A novel and generic algorithm was developed to correct for the variation of retention time and mass-to-charge dimensions between two maps. It uses an adapted pose clustering approach [31,32] to efficiently superimpose raw maps as well as feature maps. In Fig. 6 two feature maps are shown. In the left plot the retention times and the mass-to-charge ratio of corresponding features vary extremely and corresponding ion species are hard to determine. However, after the mapping of the two feature maps onto a consistent coordinate system the correspondence between the two maps can easily be seen in the right plot.


OpenMS - an open-source software framework for mass spectrometry.

Sturm M, Bertsch A, Gröpl C, Hildebrandt A, Hussong R, Lange E, Pfeifer N, Schulz-Trieglaff O, Zerck A, Reinert K, Kohlbacher O - BMC Bioinformatics (2008)

Map alignment example. Left: Two feature maps with varying retention time and mass-to-charge dimensions. Right: The features of the second feature maps were transformed onto the coordinate system of the first feature map.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2311306&req=5

Figure 6: Map alignment example. Left: Two feature maps with varying retention time and mass-to-charge dimensions. Right: The features of the second feature maps were transformed onto the coordinate system of the first feature map.
Mentions: OpenMS offers algorithms to align multiple experiments and to match the corresponding ion species across many samples. A novel and generic algorithm was developed to correct for the variation of retention time and mass-to-charge dimensions between two maps. It uses an adapted pose clustering approach [31,32] to efficiently superimpose raw maps as well as feature maps. In Fig. 6 two feature maps are shown. In the left plot the retention times and the mass-to-charge ratio of corresponding features vary extremely and corresponding ion species are hard to determine. However, after the mapping of the two feature maps onto a consistent coordinate system the correspondence between the two maps can easily be seen in the right plot.

Bottom Line: Although software tools for many data analysis tasks are available today, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow.OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis.This has already been demonstrated in several studies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Bioinformatics, Eberhard Karls University Tübingen, Sand 14, 72076 Tübingen, Germany. sturm@informatik.uni-tuebingen.de

ABSTRACT

Background: Mass spectrometry is an essential analytical technique for high-throughput analysis in proteomics and metabolomics. The development of new separation techniques, precise mass analyzers and experimental protocols is a very active field of research. This leads to more complex experimental setups yielding ever increasing amounts of data. Consequently, analysis of the data is currently often the bottleneck for experimental studies. Although software tools for many data analysis tasks are available today, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow.

Results: We present OpenMS, a software framework for rapid application development in mass spectrometry. OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis. This has already been demonstrated in several studies.

Conclusion: OpenMS is available under the Lesser GNU Public License (LGPL) from the project website at http://www.openms.de.

Show MeSH
Related in: MedlinePlus