pyTRACTnmr 1.0.0

A simple gui based application to process and analyse TRACT data from NMR spectroscopy.

pyTRACTnmr

pyTRACTnmr is a graphical user interface (GUI) application designed for the processing and analysis of TRACT (TROSY for Rotational Correlation Times) experiments in NMR spectroscopy. It provides a streamlined workflow to go from raw Bruker data to calculated rotational correlation times ($\tau_c$) with robust error estimation. All calculations are based on TRACT revisited: an algebraic solution for determining overall rotational correlation times from cross-correlated relaxation rates DOI:10.1007/s10858-021-00379-5.

Note: Currently this only supports data collected with Bruker spectrometers using pulseprogram tractf3gpphwg.

Features

• Bruker Data Import: Directly load Bruker experiment directories.
• Interactive Processing:
  • Phase correction (0th and 1st order).
  • Apodization (Sine Bell, Exponential) and Zero Filling.
  • Baseline correction with manual node picking.
• Relaxation Analysis:
  • Automatic splitting of Pseudo-2D experiments into $\alpha$ (Anti-TROSY) and $\beta$ (TROSY) states.
  • Exponential decay fitting to determine relaxation rates ($R_\alpha$, $R_\beta$).
  • Calculation of $\tau_c$ with error estimation using bootstrapping.
• Sliding Window Analysis: Perform $\tau_c$ calculation across the spectral width to identify domain dynamics.
• Visualization: Interactive Matplotlib plots for spectra, decay fits, and sliding window results embedded in a Qt interface.
• Export: Save results to CSV and generate Python scripts for publication-quality plotting.

Installation

Prerequisites

• Python 3.14 or higher recommended (Though it is not tested it should run with earlier version of Python 3).
• uv (optional, but recommended for building).

Installation

Quick Start with uv

The fastest way to try pyTRACTnmr without installation is:

uvx pyTRACTnmr

Using pip

pip install pyTRACTnmr

From Source

1. Clone the repository:

   git clone https://github.com/debadutta-patra/pyTRACTnmr.git
   cd pyTRACTnmr
   

2. Install the package:

   Using uv (fastest):

   uv pip install .
   

   Using standard pip:

   pip install .
   

Usage

Launching the App

After installation, you can start the application from the terminal:

pytractnmr

Or run it as a python module:

python -m pyTRACTnmr.main

Analysis Workflow

1. Load Data: Click "Load Bruker Directory" and select your experiment folder.
2. Process:
   • Use the Processing tab to adjust phase correction sliders.
   • Drag the green selection box on the top spectrum plot to define the integration region (Start/End ppm).
   • Select nodes for polynomial baseline correction using the Pick Nodes button.
3. Fit:
   • Switch to the Fitting tab.
   • Input experimental parameters (Field Strength, CSA, etc.).
   • Set the number of Bootstraps (e.g., 1000).
   • Click "Calculate Tau_c".
   • (Optional) Check the sliding window analysis to calculate $\tau_c$ across the spectral width.
4. Export:
   • Right-click the results table to Export Table to CSV.
   • Click the export options in Fitting tab to generate a CSV file and python script for publication-quality plotting.

Dependencies

• PySide6
• numpy
• scipy
• matplotlib
• nmrglue

License

This project is licensed under the GNU General Public License v3.0 License - see the LICENSE file for details.