2019-09-05 –, Track 3 (Oteiza)
This talk is about emzed, a Python library to support biologists with little programming knowledge to implement ad-hoc analyses as well as workflows for mass-spectrometry data.
Many of the existing mass spectrometry data analysis tools are desktop applications designed for specific applications without support for customization. In addition, many of the commercial solutions offer no or only limited functionality for exporting results.
In addition, the existing programming libraries in this area are scattered across different languages, mostly R, Java and Python.
As a result, data analysis in this area often consists of manual import/export steps from/to various tools and self-developed scripts that prevent the reproducibility of results obtained or automated execution on high-performance infrastructures.
emzed tries to avoid these problems by integrating existing libraries and tools from Python, R (and in the near future also Java) into an easy-to-use API.
To support workflow development and increase confidence in end results
emzed also offers tools for interactive visualization of mass spectrometry related data structures.
The presentation introduces basics and concepts of emzed, some lessons learned and current development of the next version of emzed.
emzed: reproducible LCMS analysis with Python the easy way
Python Skill Level –basic
Domain Expertise –none
Domains –Data Visualisation, Open Source,
- master in mathematics 1994 at University of Saarbrücken, Germany.
- PHD in applied mathematics since 2001 at University of Saarbrücken, Germany.
- Postdoc position until 2008 at University of Saarbrücken
- 2008-2014 working as software developer and data scientist for mineway GmbH
- since 2014 senior software developer at Scientific IT Services of ETH Zurich, Switzerland.