Skip to content

This repository contains all code used to predict transformation products (TPs) and to perform all analyses reported in the publication by Trostel et al., 2023

License

Notifications You must be signed in to change notification settings

FennerLabs/TP_predict

Repository files navigation

TP_predict - Predict TPs and create suspect lists

This collection of scripts allows the user to reproduce the TP prediction and data analyses presented in the following publication:

Trostel, L., Coll, C., Fenner, K., and Hafner, J. (2023). Combining predictive and analytical methods to elucidate pharmaceutical biotransformation in activated sludge. Environ. Sci.: Processes Impacts 25, 1322–1336. https://doi.org/10.1039/D3EM00161J

The tools can further be used to perform the same predictions and analyses on a different set of compounds.

Content

  • TP_prediction: Script to predict TPs and corresponding biodegradation pathways
  • File_conversion: Conversion of prediction output to input for suspect screening tools
    • Prediction_output_to_mass_list
    • SMILES_to_mass_and_inclusion_list
  • Additional_analyses
    • Compare_methods
    • Analyse_cutoff_thresholds

Specific user guidance can be found in the README.md files of the content folders.

How to

To fetch the code from the git repository, open a terminal and run:

$ git clone https://github.com/FennerLabs/TP_predict

Go to the newly created directory:

$ cd TP_predict

To set up TP_predict and install the dependencies, run:

$ make

Installation and requirements

The scripts requires rdkit for python, which is easiest installed in a conda environment. All scripts have been developed and tested in Python version 3.6 on Mac, Linux and Windows operating systems.

Anaconda step by step guide for non-python users:

  1. Download Anaconda and install it, then run Anaconda Navigator
  2. create new environment under the Environment tab, select python version 3.6.13
  3. go to environments, click play button on newly created environment, open Terminal
  4. run following lines individually (need to confirm: type y and press enter)(might take a while): conda install -c rdkit rdkit and pip install pubchempy
  5. check if pandas is installed and active according to this Tutorial
  6. open Anaconda Navigator, go to Home tab, check if Applications on is set to the new environment
  7. click gear icon on Spyder > install specific version > 5.0.5 and wait for installation to finish
  8. click launch button below Spyder

About

This repository contains all code used to predict transformation products (TPs) and to perform all analyses reported in the publication by Trostel et al., 2023

Resources

License

Stars

Watchers

Forks

Packages

No packages published