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 --gene-finding-only

Important

As of ggCaller v1.4, we highly recommend running ggCaller with --gene-finding-only enabled. This will not conduct annotation or COG clustering, and will instead generate a directory of GFF files which can be used in any modern clustering method, such as Panaroo. Future versions will remove panaroo entirely.

To run ggCaller with just reads:

ggcaller --reads input.txt --out output_path --gene-finding-only

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 <path to files>:/data samhorsfield96/ggcaller:latest ggcaller --balrog-db /app/ggc_db --refs /workdir/input_docker.txt --out /workdir/output_path --gene-finding-only

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 <path>.