1 General¶

The emzed concept¶

1. Analysis workflows are Python scripts composing mainly emzed modules. Single processing steps are explicit and clear which supports reproducible research.

2. We choose Python as this makes programming with emzed3 as simple as possible.

3. emzed ships with Spyder 4 providing an integrated development environment (IDE) to support the use of emzed modules and the overall development process.

4. In order to strengthen the trust in analysis results, emzed provides interactive visualization tools for intermediate and final results. Thus, an emzed workflow can deliver more information than just a bunch of numbers or static plots.

5. emzed cherry picks algorithms form established libraries like OpenMS or MZmine 2.

6. emzed is directly connected to pandas and its ecosystem featuring straightforward application of i.e. advanced statistics, machine learning, or data visualization.

What is new in emzed3?¶

emzed3 is a further development of eMzed and emzed2 that was based on deprecated Python2.

• emzed3 is now based on Python3.

• improved LC-MS data visualization i.e. color coding of rows and spectra.

• improved MS level 2 data processing with new emzed module ms2 with i.e. MS2 spectra export to SIRIUS.

• emzed3 provides an extension to use the feature finding algorithm of MZmine2.

• emzed3 is fully scalable and features parallel computing.

• emzed3 internaly uses sqlite to allow fast routine operations on huge data sets.

IMPORTANT NOTES: - Although many former eMZed and emzed2 concepts were kept, fundamental data structures have been replaced and hence workflows built with emzed2 are no longer executable in the emzed3 environment.

• Accordingly, ``*.table`` files created with former emzed frameworks are no longer compatible.

• emzed2 is no longer maintained.

Why should one build his own LC-MS workflows?¶

• Understand what is going on with your data while processing!!

• Shape your workflows to your individual problems.

• Fast adaptation of workflows to different LC-MS instruments.

• Test and develop new analytical strategies.

Required (Python) programing skills¶

• You are familiar with the following basic data types: str, int, float, bool or iterables like list and tuple.

• You should be familiar with Python dictionaries.

• You know the basic control statements if, elif, else and you are familiar with for and while loops.

• You should know how to call functions and methods and it is advantageous if you know how to write (simple) functions.