Quickstart ================================== Installation ------------ The easiest way to get up and running is using Docker. To get up and running, pull the latest image:: docker pull samhorsfield96/ggcaller:latest Preparing the data ------------------ Place all of your samples to be analysed in the same directory. Then navigate inside and run:: ls -d -1 $PWD/*.fasta > input.txt If using Docker, instead navigate to the directory containing the fasta files and run the below command, to ensure file paths are relative (the docker version will not work with absolute paths):: ls -d -1 *.fasta > input_docker.txt Then, append the prefix ``/data/`` to each line to enable ggCaller to find the files:: sed -i -e 's|^|/data/|' input_docker.txt Running ggCaller ------------------ .. important:: Assemblies with many Ns generate disjointed DBGs leading to underclustering. To ensure optimal performance, avoid using assemblies containing Ns. To run ggCaller with just assemblies:: ggcaller --refs input.txt --out output_path To run ggCaller with just reads:: ggcaller --reads input.txt --out output_path If using Docker, run with the below command, ensuring you keep ``--balrog-db /app/ggc_db`` and ``/workdir`` paths as specified below. Replace ``path to files`` with the absolute path to the directory of files in ``input_docker.txt``:: docker run --rm -it -v $(pwd):/workdir -v :/data samhorsfield96/ggcaller:latest ggcaller --balrog-db /app/ggc_db --refs /workdir/input_docker.txt --out /workdir/output_path .. important:: We haven't extensively tested calling genes within read datasets yet. Exercise caution when interpreting results. Results will be saved to the directory ``ggCaller_output`` by default. To change this, specify ``--out ``.