README.md

pymgpipe |

Coverage Report

File	Stmts	Miss	Cover	Missing
pymgpipe
coupling.py	39	6	85%	20, 43, 46–47, 52, 67
diet.py	103	19	82%	16, 22, 396–397, 437–453, 466–477, 482–485, 494, 496, 525
fva.py	144	59	59%	32, 36, 88–92, 98, 107–113, 116–117, 120–121, 139–149, 165, 174–235, 244
io.py	106	37	65%	17, 55, 61–66, 80–81, 95–96, 108, 111, 117–120, 125–133, 142, 146–147, 152–157, 161–167, 176–177
main.py	148	44	70%	112, 115, 167, 210–212, 243–297, 304, 309–310, 323
metrics.py	24	21	12%	5–35
modeling.py	145	7	95%	36, 39, 54–57, 129, 131
nmpc.py	64	5	92%	95, 132–134, 136
utils.py	235	107	54%	45–46, 49, 52, 67, 73, 83, 87, 102–105, 111, 115–117, 120–138, 142–152, 160, 173–174, 176–177, 199–200, 205–207, 245–248, 250–264, 270, 281–286, 289–293, 313–314, 325–367
pymgpipe/tests
test_e2e.py	90	1	99%	197
TOTAL	1309	306	77%

API Docs

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

Installation

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

Additional Dependencies

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.

Inputs

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.

Outputs

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-

File	Type	Description
reaction_content	CSV	Matrix showing binary presence/absence of all reactions within each sample
reaction_abundance	CSV	Matrix showing scaled abundance (between 0 and 1) of all reactions within each sample
sample_label_conversion	CSV	Dictionary with conversion between original sample names and model names (default sample_prefix is 'mc')
metabolic_diversity	PNG	Plot depicting # of unique reactions & taxa present within each sample
problems	dir	Directory containing LP problems (default format is .mps, with compressed set to True)
models	dir	Directory containing COBRA moddels (default format is .xml, with compressed set to True)

Examples

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

Attribution

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

Contributing

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!

Reporting Issues

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.