Sismis
Machine learning-based secretion system annotation tool
🦇 Overview
Sismis (secretion system discovery tool; pronounced shish-mish) is a machine learning (ML)-based tool for detecting and classifying secretion systems in prokaryotic (meta)genomes.
🔍 Quickstart
To detect secretion systems in an assembled prokaryotic (meta)genome:
sismis run -g [fasta] -o [output directory] [options...]
For help/to view all options:
sismis -h
🔧 Installation
Sismis and its dependencies can be installed via pip:
pip install sismis
⚙️ Usage and options
Command structure
sismis run -g [fasta] -o [output directory] [options...]
Required arguments
-g <file>, --genome <file> a genomic file containing one or more
sequences to use as input. Must be in
one of the sequences format supported
by Biopython.
🔖 Citation
If you found Sismis useful, please cite our preprint! 🤗
To cite Sismis and/or the Sismis Atlas:
Martin Larralde, Florian Albrecht, Josefin Blom, Johan Henriksson, Laura M Carroll. 2025. Scalable and interpretable secretion system annotation with Sismis. bioRxiv 2025.09.09.675188. doi: https://doi.org/10.1101/2025.09.09.675188.
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