What is emzed ?

emzed is an open source toolbox for rapid and interactive development of LCMS data analysis workflows in Python.

What does this mean ?

emzed makes experimenting with new analysis strategies for LCMS data as simple as possible.

Fundamental principles of emzed

  1. Analysis workflows are Python scripts composing emzed modules. Single processing steps are explicit and clear which supports reproducible research.
  2. We choose Python which makes programming with emzed as simple as possible.
  3. In order to strengthen the trust in analysis results, emzed provides interactive visualization tools for intermediate and final results. So an emzed workflow can deliver more information than just a bunch of numbers or static plots.
  4. emzed ships with emzed workbench which is an integrated development environment (IDE) to support the use of emzed modules and the overall development process.


You find some slides about emzed and how the story started at http://emzed.ethz.ch/presentation.

Development goals

  • When we started to implement own analysis workflows we found that the software landscape was almost divided into two classes: On the one side there exist fast and flexible frameworks, but in languages as C++ which only can be used efficiently by experienced programmers. On the other hand, there are applications with graphical user interfaces that are simple to use and learn but hard to modify for special needs.

    Our primary goal has been to develop a framework which combines the positive aspects of the two extremes.

  • The invention of programming environments as Matlab and R leveraged the productivity of mathematicians and scientists from other fields. We try to introduce this concept for analyzing LCMS data.

    emzed is based on Spyder [spyderlib] for providing the IDE and [guiqwt] and [guidata] for plotting.

  • Instead of reinventing the wheel we cherry pick algorithms from established libraries and frameworks as [openms] and [xcms]. These are wrapped behind a consistent application programming interface (API) and thus emzed based workflows avoid manual and error prone import and export steps.

emzed in the press

Recent publications using emzed for data analysis:

  • Hartl et al., “Longevity of major coenzymes allows minimal de novo synthesis in microorganisms”, Nature Microbiology, 2017, http://dx.doi.org/10.1038/nmicrobiol.2017.73
  • Hemann et al. “The One-carbon Carrier Methylofuran from Methylobacterium extorquens AM1 Contains a Large Number of Alpha- and Gamma-linked Glutamic Acid Residues”, http://doi.org/10.1074/jbc.M116.714741
  • Peter et al. “Screening and Engineering the Synthetic Potential of Carboxylating Reductases from Central Metabolism and Polyketide Biosynthesis.” Angew Chem Int Ed Engl. (2015).
  • Kiefer, Patrick, et al. “DynaMet, a fully automated pipeline for dynamic LC-MS data.” Analytical Chemistry (2015).
  • Ryffel, Florian, et al. “Metabolic footprint of epiphytic bacteria on Arabidopsis thaliana leaves.” The ISME journal (2015).
  • Müller, Jonas EN, et al. “Core pathways operating during methylotrophy of Bacillus methanolicus MGA3 and induction of a bacillithiol-dependent detoxification pathway upon formaldehyde stress.” Molecular microbiology (2015).
  • Müller, Jonas EN, et al. “Engineering Escherichia coli for methanol conversion.” Metabolic engineering 28 (2015): 190-201.
  • Wilson, Micheal C., et al. “An environmental bacterial taxon with a large and distinct metabolic repertoire.” Nature 506.7486 (2014): 58-62.
  • Erb, Kiefer, et al. “GFAJ-1 is an arsenate-resistant, phosphate-dependent organism”, Science (2012).

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