Download autoMLST2

autoMLST2 is free and open-source with no login requirement. It can also be used as a stand-alone application:

  • Download the AutoMLST2 pipeline codes
  • Download Files

    Click the links below to download the reference database:


    How to Use the Stand-Alone Version of AutoMLST2

    Follow these steps to set up and run the AutoMLST2 stand-alone version on your local unix-based machine:

    1. Download and Prepare the Files

    1. Download the AutoMLST2 pipeline code from above and extract it. This will create a directory named:
      AutoMLST2_standalone/
    2. Download the Bacteria Mash Database and place it inside:
      AutoMLST2_standalone/automlst2/
    3. Download the Reference Database (Bacteria_db.zip), extract it, and move the entire resulting Bacteria_db/ folder into:
      AutoMLST2_standalone/automlst2/

    2. Build the Docker Image

    1. Open a terminal window.
    2. Navigate to the pipeline directory:
      cd AutoMLST2_standalone/automlst2/
    3. Build the Docker image (this may take several minutes):
      docker-compose build --no-cache

    3. Run Analysis Jobs

    1. For each job, create a folder inside the uploads directory and place your genome files there:
      AutoMLST2_standalone/uploads/job_input/
    2. Choose an output folder name (e.g. job_output). It will be created automatically in:
      AutoMLST2_standalone/results/
    3. Run the analysis with this command (replace /absolute/path/to/AutoMLST2_standalone/ with your actual path):
      docker run --rm -it \
        -v /absolute/path/to/AutoMLST2_standalone/uploads:/uploads \
        -v /absolute/path/to/AutoMLST2_standalone/results:/results \
        -v ./Bacteria_db:/app/Bacteria_db:ro \
        -v ./filtered_hmm.LIB:/app/filtered_hmm.LIB:ro \
        automlst2_backend \
        /uploads/job_input /results/job_output
    4. To view additional command-line options, run:
      docker run automlst2_backend --help

    Note: The analysis results will be available in the output folder specified. The final tree can be found at results/job_output/final.tree.