Install from source

First of all, download the gutSMASH python source from our GitHub repo: https://github.com/victoriapascal/antismash/tree/gutsmash

Then, make sure you have the following gutSMASH dependencies installed:

• hmmer3 (version 3.0)
• fasttree (version 2.1.7 tested)
• diamond (0.8.36 tested)
• muscle (version 3.8.31 tested)
• prodigal (version 2.6.1 tested)
• NCBI blast+ (version 2.2.31 tested)
• python (version 3.7.6 tested, anything >= python 3.0 should work)
• python-virtualenv (not needed, but highly recommended)

You can use apt-get to install the dependencies in Linux machines:

sudo apt-get install hmmer2 hmmer diamond-aligner fasttree prodigal ncbi-blast+ muscle glimmerhmmsource as3/bin/activate

Or Homebrew for macOS systems:

brew install hmmer2 hmmer diamond fasttree prodigal blast muscle brewsci/science/glimmerhmmsource as3/bin/activate

All the python dependencies can be installed using a simple command:

pip3 install biopython helperlibs bcbio-gff pysvg-py3 scikit-learn matplotlib pyScss Jinja2

To run gutSMASH, there are 3 databases that need to be found in gutsmash/antismash/databases:

• The latest (processed) Pfam database Pfam-A.hmm.gz available from the Pfam FTP website ( https://www.ebi.ac.uk/interpro/download/pfam/), and hmmpressed using the HMMER suit (http://hmmer.org)
• The ClusterBlast database, which can be downloaded and uncompressed from here: ClusterBlast.zip
• The resfam database, which can be downloaded and uncompressed from here: resfam.zip

Next, the smcogs database that needs to be place in gutsmash/antismash/detection/genefunctions/gut_data can be downloaded from here smcogs.hmm.zip. Then, use hmmpress before using it.

Finally, the KnownClusterBlast database that needs to be place in gutsmash/antismash/modules/clusterblast/data/known can be downloaded and uncompressed from here: KnownClusterBlast.zip

For more information on how to run gutSMASH visit the README in our GitHub