Quickstart#

Important

We are aware of issues installing from conda version at the moment. We recommend installing via Docker at this time.

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 you samples to analyse 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.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. You must ensure all paths are relative, including in input.txt:

docker run --rm -it -v $(pwd):/workdir samhorsfield96/ggcaller:latest ggcaller --refs input.txt --out 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 <path>.