NPLinker

Data mining microbial natural products by integrating genomics and metabolomics data

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What NPLinker can do for you

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Natural Products Linker (NPLinker)

NPLinker is a python framework for data mining microbial natural products by integrating genomics and metabolomics data.

Original paper: Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions.

Setup and usage

Requirement

Installation

NPLinker is a python package, using both pypi packages and non-pypi packages as dependencies. It requires ~4.5GB of disk space to install all the dependencies.

# Check python version (requiring ≥3.9)
python --version

# Create a new virtual environment
python -m venv env
source env/bin/activate

# install from nplinker releases (requiring ~300MB of disk space)
pip install --pre nplinker

# or install the latest from source code
pip install git+https://github.com/nplinker/nplinker@dev 

# install nplinker non-pypi dependencies and databases (~4GB)
install-nplinker-deps

A virtual environment is required to install the the non-pypi dependencies. You can also use conda to manage python environments.

Testing

To run the tests, you need to clone this repo and install the development dependencies:

# Create a new virtual environment
python -m venv env
source env/bin/activate

# Clone the repository and install the development dependencies
git clone https://github.com/NPLinker/nplinker.git
cd nplinker
pip install -e ".[dev]"
install-nplinker-deps

Unit tests

To run the unit tests, you can use the following command:

pytest

Pytest will use all available CPU cores to run the unit tests in parallel.

Integration tests

To run the integration tests, you can use the following command:

pytest -n1 tests/integration

The -n1 is to use one CPU core to run the tests. Change it to -n2 if you want to use two CPU cores to run in parallel.

Usage

See the documentation for more information about how to use NPLinker.

Contributing

If you want to contribute to the development of nplinker, have a look at the contribution guidelines and README for developers.

Keywords
Programming languages
  • Jupyter Notebook 99%
  • Python 1%
License
</>Source code
Packages
pypi.org

Participating organisations

Netherlands eScience Center
Wageningen University & Research

Contributors

GC
Giulia Crocioni
Engineer
Netherlands eScience Center
HH
Helge Hecht
JvdH
Justin J. J. van der Hooft
AD
Arjan Draisma
Developer
Wageningen University & Research

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A community-supported workflow connecting microbial genes, and organisms to their molecular products

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