OpenMS – An open-source software framework for mass spectrometry

By Marc Sturm, A. Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, A. Zerck, Knut Reinert and 1 more. BMC Bioinformatics, 2008

646 citations recorded by the source corpus.

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

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/d9970b7eb0ed2c38ea7d00a3937d59075e41cd88

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Citations in the corpus

xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data (2013, background): “Lange et al. [8] reported that XCMS [9] performs better or comparable to other LC/ MS alignment tools such as msInspect [10], MZmine [11,12], OpenMS [13,14], SpecArray [15], and XAlign [16] for the analysis of metabolomics data.”
mzML—a Community Standard for Mass Spectrometry Data (2010, background): “OpenMS (26), an open-source C (cid:5)(cid:5) library for mass spectrometry, also provides classes for reading and writing mzML which can be easily integrated in other software tools.”
Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis (2016, methodology): “This pre-processing step can be done by any number of locally installable, freely available MS spectral processing tools such as MetAlign (Lommen, 2009), OpenMS (Sturm et al., 2008), MZmine (Katajamaa et al., 2006), XCMS (Smith et al., 2006), XCMS-Online (Tautenhahn et al., 2012), and MS-DIAL (Tsuga”
Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial (2018, neutral): “These include for example OpenSWATH (Rost et al , 2014) (part of OpenMS, Rost et al , 2016b; Sturm et al , 2008), Skyline (MacLean et al , 2010), PeakView (SCIEX) and Spectronaut (Bruderer et al , 2015) (Biognosys).”
Expression Atlas update—an integrated database of gene and protein expression in humans, animals and plants (2015, methodology): “Raw data was converted to mzML format and was processed in an OpenMS workflow (3).”