Installation and configuration

TOGA is compatible with both Linux and MacOS systems, including M1-based machines. While it is highly recommended to have access to a computational cluster for larger tasks, small or partial genomes with short genes can be processed on a desktop PC.

TOGA operates properly with Python versions 3.9 and above.

The required Python packages are listed in the requirements.txt file and are also provided below:

• twobitreader==3.1.7
• networkx==3.1
• pandas==2.0.2
• numpy==1.24.3
• xgboost==1.7.5
• scikit-learn==1.2.2
• joblib==1.2.0
• h5py==3.8.0

Typically, these packages can be installed without any issues. However, if you encounter any difficulties with XGBoost, please refer to the Troubleshooting section (still under development; currently explained in the README.md).

Furthermore, TOGA requires nextflow to run parallel jobs.

You can install Nextflow using one of the following methods:

curl -fsSL https://get.nextflow.io | bash
# OR
conda install -c bioconda nextflow

If you've downloaded Nextflow using curl, move the Nextflow executable to a directory that's accessible via your $PATH variable. Please note that Nextflow requires Java >=8.

TOGA employs CESAR2.0 to generate structural orthologs annotations. There is no need for manual installation, as the configure.sh script will handle this process.

In addition, the script will train models for chain classification and compile all necessary binaries written in C.

Nextflow

To write about custom configurations. Also, about custom strategy class if nextflow does not fit (will be relevant for 1.1.5)

relevant issues: probably solved

issues that cannot be addressed directly: user's system limitations