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:

• Download Bacteria Reference Database (16GB Bacteria_db.zip)
• Download Bacteria Mash Database (4GB .msh file) - This is a large file (4GB) and may take some time to download

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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.