MGP prediction

How to install

It works on Linux operating system and has been tested on Ubuntu 16.04. The runtimes below are generated using a computer with the specs (32 GB RAM, Intel(R) Core(TM) i7-4790 CPU @ 3.60 GHz) and internet of speed around 80 Mbit/s.

  1. Clone the repository

    git clone https://bitbucket.org/kaistsystemsbiology/mgp_prediction.git

  2. Create and activate a conda environment

    cd mgp_prediction
conda env create -f environment.yaml
source activate MGPprediction

which should install in about 2 minutes

Implementation 1. Create .csv file for flux (e.g.,exampleFlux.csv) and mutation (e.g.,exampleMutation.csv). Please referred to the format of each file in exampleInput directory.

  1. Run MGP prediction. The following arguments are required: -o/–output_dir, -f/–flux, -mut/–mutation

    Example .. code-block:: bash

    mkdir output python runMGPprediction.py -o ./output -f ./exampleInput/exampleFlux.csv -mut ./exampleInput/exampleMutation.csv

    The output file “predictedMGPs.csv” will be generated in output directory after computation. The run time for this source code on example input is about 90 seconds.

  2. The output file is in .csv format and consists of four columns (i.e., Target gene, Target metabolite and its MetaNetX ID, and Target pathway) which represent information of predicted MGPs.

Reference Lee, G., Lee, S.M., Lee, S. et al. Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data. Genome Biol 25, 66 (2024). https://doi.org/10.1186/s13059-024-03208-8