OpenMS - an open-source software framework for mass spectrometry

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.

Figure 1

The overall design of OpenMS.

Figure 2

The data reduction concept of OpenMS. A raw map (top) which is first reduced to a peak map (middle) and finally to a feature map (bottom). The direct reduction of raw to feature map is also possible.

Figure 3

Visualization widget examples. (a) Visualization of a raw data spectrum and the corresponding peaks spectrum as two superimposed layers. (b) Part of an HPLC-MS map displayed in a 2D view.

Figure 4

Signal processing example. Result of baseline reduction and peak picking: From the raw spectrum (left) the baseline is subtracted (middle) and then peaks are picked (right).

Figure 5

The OpenMS feature model. The averagine model (left) and the corresponding isotope wavelet (right) used by our algorithm. (Shown for mass ~2000 Da and charge 1.).

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.