Metadata-Version: 2.1
Name: q2-micom
Version: 0.11.1
Summary: QIIME 2 plugin for metabolic modeling of microbial communities.
Home-page: https://github.com/micom-dev/q2-micom
Author: Christian Diener
Author-email: mail@cdiener.com,
License: Apache License 2.0
Description: <img src="docs/assets/logo.png" width="75%">
        
        [![Test and deploy](https://github.com/micom-dev/q2-micom/actions/workflows/test_package.yml/badge.svg)](https://github.com/micom-dev/q2-micom/actions/workflows/test_package.yml)
        [![codecov](https://codecov.io/gh/micom-dev/q2-micom/branch/master/graph/badge.svg)](https://codecov.io/gh/micom-dev/q2-micom)
        [![PyPI version](https://badge.fury.io/py/q2-micom.svg)](https://badge.fury.io/py/q2-micom)
        
        
        A QIIME 2 plugin for MICOM.
        
        ## Installation
        
        You will need an existing QIIME 2 environment. Follow the instructions on ([how to install QIIME 2](https://docs.qiime2.org/2021.2/install/native/#install-qiime-2-within-a-conda-environment))
        otherwise. Let's assume that environment was called `qiime2-2021.2` for all further steps.
        
        ### Add q2-micom to the QIIME 2 environment
        
        This will be the same step for any supported QIIME 2 version or operating systems.
        
        ```bash
        wget https://raw.githubusercontent.com/micom-dev/q2-micom/master/q2-micom.yml
        conda env update -n qiime2-2021.2 -f q2-micom.yml
        # OPTIONAL CLEANUP
        rm q2-micom.yml
        ```
        
        Finally, you activate your environment.
        
        ```bash
        conda activate qiime2-2021.2
        ```
        
        ### Install a QP solver
        ### Install a QP solver
        
        **CPLEX (recommended)**
        
        *QIIME 2 is only compatible with CPLEX 12.10 or earlier (later version require at least Python 3.7).*
        
        After registering and downloading the CPLEX studio for your OS unpack it (by running the provided installer) to a directory of your choice (we will assume it's called `ibm`).
        
        Now install the CPLEX python package into your activated environment:
        
        ```bash
        pip install ibm/cplex/python/3.6/x86-64_linux
        ```
        
        Substitute `x86-64_linux` with the folder corresponding to your system (there will only be one subfolder in that directory).
        
        **Gurobi**
        
        Gurobi can be installed with conda.
        
        ```bash
        conda install -c gurobi gurobi
        ```
        
        You will now have to register the installation using your license key.
        
        ```bash
        grbgetkey YOUR-LICENSE-KEY
        ```
        
        Note that Gurobi support is often iffy and might break for periods of time. It will also be *much* slower than CPLEX.
        
        ### Finish your installation
        
        If you installed `q2-micom` in an already existing QIIME 2 environment, update the plugin cache:
        
        ```bash
        conda activate qiime2-2021.2  # or whatever you called your environment
        qiime dev refresh-cache
        ```
        
        You are now ready to run `q2-micom`!
        
        ## Usage
        
        Here is a graphical overview of a `q2-micom` analysis.
        
        <img src="docs/assets/overview.png" width="100%">
        
        The best way to get started is to work through the [community tutorial](https://micom-dev.github.io/q2-micom).
        
        ## Supported QIIME 2 versions
        
        `q2-micom` is tested against:
        
        1. the current [QIIME 2 version](https://docs.qiime2.org/)
        2. the previous version
        
        It should also work with
        
        3. the [development version](https://dev.qiime2.org/latest/)
           however, we don't test it in the CI as it occasionally breaks
        
        
        ## References
        
        MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota <br>
        Christian Diener, Sean M. Gibbons, Osbaldo Resendis-Antonio <br>
        mSystems 5:e00606-19 <br>
        https://doi.org/10.1128/mSystems.00606-19
        
Keywords: microbiome,modeling,metabolism,community
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
