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JeanMainguy committed Jan 25, 2024
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27 changes: 27 additions & 0 deletions paper/paper.bib
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Expand Up @@ -180,3 +180,30 @@ @article{metagWGS_inprep

}

@article{gruning2018bioconda,
title={Bioconda: sustainable and comprehensive software distribution for the life sciences},
author={Gr{\"u}ning, Bj{\"o}rn and Dale, Ryan and Sj{\"o}din, Andreas and Chapman, Brad A and Rowe, Jillian and Tomkins-Tinch, Christopher H and Valieris, Renan and K{\"o}ster, Johannes and Bioconda Team},
journal={Nature methods},
volume={15},
number={7},
pages={475--476},
year={2018},
publisher={Nature Publishing Group US New York},
doi = {10.1038/s41592-018-0046-7},
}


@article{Bioconda:2018,
title = {Bioconda: Sustainable and Comprehensive Software Distribution for the Life Sciences},
shorttitle = {Bioconda},
author = {Gr{\"u}ning, Bj{\"o}rn and Dale, Ryan and Sj{\"o}din, Andreas and Chapman, Brad A. and Rowe, Jillian and {Tomkins-Tinch}, Christopher H. and Valieris, Renan and K{\"o}ster, Johannes},
year = {2018},
month = jul,
journal = {Nature Methods},
volume = {15},
number = {7},
pages = {475--476},
publisher = {{Nature Publishing Group}},
issn = {1548-7105},
}

9 changes: 9 additions & 0 deletions paper/paper.md
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Expand Up @@ -45,5 +45,14 @@ Bin completeness and contamination are assessed using CheckM2 [@chklovski2023che

Binette serves as the bin refinement tool within the [metagWGS](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs) metagenomic analysis pipeline [@metagWGS_inprep], providing a robust and faster alternative to the bin refinement module of the metaWRAP pipeline as well as other similar bin refinement tools.

# Availability

Binette is accessible through [PyPI](https://pypi.org/project/Binette/), and a Conda [package](https://anaconda.org/bioconda/binette) can be found in the Bioconda channel [gruning2018bioconda]. The source code for Binette is available on [GitHub](https://github.com/genotoul-bioinfo/binette) under the MIT license. The GitHub repository includes continuous integration tests, test coverage, and employs continuous deployment through GitHub actions.


# Acknowledgements

We would like to thank Matthias Zytnicki for his valuable insights and support during the development of the binette algorithm.


# References

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