chromhandler 0.10.1

Tool for processing chromatography data

Chromhandler - handling time-resolved chromatographic data

ℹ️ Overview

chromhandler (formerly chromatopy) is a Python package that aims to streamline the data processing and analysis of time-course chromatographic reaction data. It allows processing raw or pre-processed chromatographic data, enriching it with metadata such as reaction time, temperature, pH, and initial concentrations of reaction components. Finally, the peaks of interest can be aggregated, concentrations calculated, and the time-course data for each analyte transformed to EnzymeML data.

chromhandler is designed to work seamlessly with OpenChrom, enabling batch processing of proprietary chromatographic data. After processing in OpenChrom and exporting to an open file format, the data can be further analyzed in Jupyter Notebooks using chromhandler. This allows for creating and applying calibration curves and generating EnzymeML files for subsequent data analysis. For some output formats, chromhandler provides a direct interface to read in data. For more information on the supported file formats and data preparation to use the chromhandler workflow, refer to the data preparation section.

graph LR
  AD[🌈 Chromatographic Instrument] --> CAL
  AD --> RXN

  subgraph "📁experimental_data"

      CAL["<div style='text-align:left;font-family:monospace'>
📂 calib_substrate<br>
├── mh1_10mM.json<br>
├── mh2_50mM.json<br>
└── mh3_90mM.json<br><br>
📂 calib_prod1<br>
├── prod1_10mM.json<br>
├── prod1_50mM.json<br>
└── prod1_90mM.json<br><br>
</div>"]

      RXN["<div style='text-align:left;font-family:monospace'>
📂 reaction_mh9<br>
├── mh9_1h.json<br>
├── mh9_2h.json<br>
├── mh9_3h.json<br>
├── mh9_4h.json<br>
├── mh9_5h.json<br>
├── mh9_6h.json<br>
└── mh9_12h.json
</div>"]
  end

  CAL -->|read| C_cal{"<span style='font-family:monospace'><b>chromhandler</b></span><br>"}
  RXN -->|read| C_react{"<span style='font-family:monospace'><b>chromhandler</b></span><br>"}

  cal1["<div style='text-align:left'>
Define measured molecules<br>
– retention time<br>
– PubChem CID
</div>"]

  cal2["<div style='text-align:left'>
Create calibration standard
</div>"]

  E4["Define reaction conditions"]
  E3["Add measured molecules"]
  E5["Define enzymes"]
  Enz[📄 EnzymeML Document]

  subgraph "Calibration mode"
    C_cal --> cal1
    cal1 --> cal2
  end

  subgraph "Reaction mode"
    C_react --> E4
    E4 --> E3
    E3 --> E5
    cal2 --> E3
  end

  E5 -->|convert| Enz

⭐ Key Features

• 🌱 Low friction data processing
  Leave behind data processing in spreadsheet applications and directly start with data analysis based on raw data.
• 🧪 Enrich reaction data with metadata
  Assign metadata like initial concentrations of reactants, temperature, pH, etc., to reaction data to yield modeling-ready data.
• 📈 Create and apply calibration curves
  Create calibrators for your analytes and use them throughout your data analysis for seamless concentration calculation.
• 📂 FAIR data
  Transform your data into EnzymeML format for subsequent analysis pipelines.

🛠️ Installation

Install chromhandler using pip:

pip install chromhandler

or

pip install git+https://github.com/FAIRChemistry/Chromhandler.git

For more information and examples, please refer to the Documentation section.