CoCoNet was tested on both MacOS and Ubuntu 18.04. To install and run CoCoNet, you will need:
- python (>=3.5, recommended: 3.7)
- pip3, the python package manager or the conda installer.
If you encounter any issue during the installation, you should retry in a fresh environment (with conda or virtualenv) with the recommended python version (3.7).
Install the latest release on PyPi¶
You can install CoCoNet, from the Python Package Index. To install it, you simply need to run the following command (you can omit –user if you’re working in a virtual environment).
# Install numpy until scikit-bio issue #1690 is resolved pip install --user numpy # Install CoCoNet pip3 install --user coconet-binning
Install the development version¶
You can also install the most up to date version with the following command:
# Install numpy until scikit-bio issue #1690 is resolved pip install --user numpy # Install CoCoNet git clone https://github.com/Puumanamana/CoCoNet.git && cd CoCoNet pip install --user .
If you encounter any issue with the development version, you should try with the latest release as the development version might not have been thoroughly checked.
Install with bioconda¶
# Install in a new environment conda create -n coconet -c bioconda -c conda-forge coconet-binning # Switch environment conda activate coconet
Alternatively, CoCoNet can be pulled directly from DockerHub. Assuming your contigs are located in /data/contigs.fasta and your indexed bam files are in /data/.bam and /data/.bai, then you can run CoCoNet with the following command:
docker run -v /data:/workspace nakor/coconet coconet run --fasta contigs.fasta --bam *.bam