LCMS data analysis made easy

emzed is an open source toolbox for rapid and interactive development of LCMS data analysis workflows in Python and makes experimenting with new analysis strategies for LCMS data as easy as possible.


How to get started

Screenshots

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Fundamental principles of emzed

  1. We choose Python which makes programming with emzed as simple as possible and approachable by LCMS experts without professional programming experience.

  2. Analysis workflows consist of Python scripts composing function calls from the emzed library. Thus processing steps are explicitly written down as Python code which is crucial for reproducible research.

  3. In order to strengthen the trust in analysis results, emzed provides interactive visualization tools for intermediate and final results. An emzed workflow can deliver more insight into the achieved results than a bunch of numbers or static plots.

  4. emzed.spyder is an integrated development environment (IDE) based on the spyder IDE tailored to support the overall development process.

Development goals

  • When we started developing LCSM analysis workflows in 2012, we realized that the existing software landscape can be divided into two groups. On the one hand there are fast and flexible frameworks, but in languages like C++, which can only be used efficiently by experienced programmers. On the other hand, there are applications with graphical user interfaces that are easy to use and learn, but difficult to adapt for special needs.

    Our goal was to develop a toolbox that combines the positive aspects of both groups.

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

  • Instead of reinventing the wheel we cherry pick algorithms from established libraries and frameworks such as OpenMs. We provide a consistent application programming interface (API) and emzed based workflows avoid manual and error prone import and export steps.

  • We split emzed into a user interface agnostic core library (also called emzed) which can be used on display less servers such as high performance computers, a library for the interactive inspection of LCMS data structures emzed.gui and the spyder based development environment emzed.spyder.

  • emzed can be extended by community extensions, right now we offer an extension emzed.ext.mzmine2 which wraps some algorithms from MZmine2.

emzed in the press

Recent publications using emzed for data analysis:

For the full list of publications continue to read here.

Original publication:

  • Kiefer Patrick, Schmitt Uwe, Vorholt Julia. eMZed: an open source framework in Python for rapid and interactive development of LC/MS data analysis workflows, Bioinformatics, Volume 29, Issue 7, 1 April 2013, Pages 963–964, https://doi.org/10.1093/bioinformatics/btt080

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