korem-lab / pymgpipe Goto Github PK

https://korem-lab.github.io/pymgpipe/

pympgipe has been built and tested with python 3.10+. To install and use our PyPi package, run pip install pymgpipe

Need at least one of the following solvers (requirements.txt includes gurobi)-

• cplex
• gurobipy

In order to install the solver interfaces in python, you can use pip install cplex or pip install gurobipy. This does not actually create a license, it just installs the python interface to interact with these solvers. Both gurobipy and cplex offer free academic licenses. To install the licenses themselves, refer to the links provided above.

To create multi-species community models with pymgpipe, you need two things to start-

• Folder with individual taxa models (either in .mat or .xml format)
• Relative abundance matrix (as a .csv) with samples as columns and taxa as rows. Taxa names should correspond to file names within taxa folder (excluding extension)

Examples of both can be found in the examples/ folder. Individual models for thousands of bacteria can be found and downloaded here.

The exact location and names of output files will vary depending on the parameters you pass into each function. However, the default output for pymgpipe's build_models function will look something like this-

* pymgpipe input*
.
├── taxaModels/
│   ├── taxa1.xml
│   ├── taxa2.xml
│   └── ...
├── abundances.csv

# pymgpipe output*
.
├── out/
    ├── reaction_content.csv
    ├── reaction_abundance.csv
    ├── sample_label_conversion.csv
    ├── metabolic_diversity.png
    ├── problems/
    │   ├── mc1.mps.gz
    │   ├── mc2.mps.gz
    │   └── ...
    └── models/
        ├── mc1.xml.gz
        ├── mc2.xml.gz
        └── ...

Here is a breakdown of each output files/directory and their descriptions-

Clone and run through workflow.ipynb in the examples/ folder (see below)

When using pymgpipe please cite-

Meydan et al., (2023). pymgpipe: microbiome metabolic modeling in Python. Journal of Open Source Software, 8(88), 5545, https://doi.org/10.21105/joss.05545

Baldini, F., Heinken, A., Heirendt, L., Magnusdottir, S., Fleming, R. M. T., & Thiele, I. (2019). The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities. Bioinformatics (Oxford, England), 35(13), 2332–2334. https://doi.org/10.1093/bioinformatics/bty941

We warmly welcome and appreciate contributions from everyone. There are several ways you can contribute:

• Reporting Bugs: If you find a bug, please create a new issue on our GitHub page. Be sure to include as much information as possible so we can reproduce and fix the bug. The more detail you provide, the better.
• Code Contributions: If you'd like to contribute code, great! Please fork this repository, make your changes in a separate branch, and then submit a pull request. We'll review your changes and discuss any necessary modifications or improvements before merging.

Here are some general guidelines for code contributions:

1. Fork the repo and create your branch from the master.
2. If you've added code, add tests.
3. Ensure the test suite passes.
4. Issue that pull request!

Issues should be reported using the GitHub issue tracker. Please check the existing issues to avoid duplicates. When reporting an issue, please provide as much detail as possible about how to reproduce the problem, including the following information:

• Operating system and version
• Details of the problem, including any error messages and screenshots if possible

Thank you for your contributions!

Copyright 2023 The Trustees of Columbia University in the City of New York. See LICENSE for additional details.