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 # 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., Hafner, J. Synergy of predictive and analytical methods advances elucidating biotransformation processes in activated sludge, 2023.
 [insert DOI]
 
 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 [insert link]
 ```
+Optional: To get the input/output data presented in the manuscript, additionally get the lfs files
+```
+$ git lfs install
+$ git lfs pull
+```
 To install the dependencies, go to the nicepath directory and run:
 ```
 $ cd TP_predict
 $ 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](https://docs.anaconda.com/anaconda/install/index.html) 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](https://docs.anaconda.com/anaconda/navigator/tutorials/pandas/)	
 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`