mocca 0.1.2

MOCCA (Multivariate Online Contextual Chromatographic Analysis) is an open-source Python project to analyze HPLC–DAD raw data.

MOCCA (Multivariate Online Contextual Chromatographic Analysis) is an open-source Python project to analyze HPLC–DAD raw data.

Automation and digitalization solutions in the field of small molecule synthesis face new challenges for chemical reaction analysis, especially in the field of high-performance liquid chromatography (HPLC). Chromatographic data remains locked in vendors’ hardware and software components limiting their potential in automated workflows and contradicting to FAIR data principles (findability, accessibility, interoperability, reuse), which enable chemometrics and data science applications. In this work, we present an open-source Python project called MOCCA (Multivariate Online Contextual Chromatographic Analysis) for the analysis of open-format HPLC–DAD (photodiode array detector) raw data. MOCCA provides a comprehensive set of data analysis features including a peak deconvolution routine which allows for automated deconvolution of known signals even if overlapped with signals of unexpected impurities or side products. By publishing MOCCA as a Python package, we envision an open-source community project for chromatographic data analysis with the potential of further advancing its scope and capabilities.

Documentation: https://mocca.readthedocs.io/en/latest/

Check out corresponding scientific publication: !!!

Installation

1. We recommend creating an isolated conda environment to avoid any problems with your installed Python packages:

   conda create -n mocca python=3.9
   conda activate mocca

2. Install mocca and its dependencies:

   pip install mocca

3. If you want to use mocca’s reporting functionality:

   pip3 install -U datapane

4. If you want to use Allotrope (adf) file format:

   pip install h5py
   pip install git+https://github.com/HDFGroup/h5ld@master

5. If you want to use mocca using JupyterLab notebooks:

   pip install jupyterlab
   ipython kernel install --user --name=mocca

Note

This project has been set up using PyScaffold 4.1.1. For details and usage information on PyScaffold see https://pyscaffold.org/.