YC
yc386/orthrus_metaproteomics
Transformer-based de novo sequencing (Casanovo) + database searching with rescoring (Sage + Mokapot). For metaproteomics datasets
Orthrus: an AI-powered, cloud-ready, and open-source hybrid approach for metaproteomics
Quick start
For cloud execution:
Click orthrus_cloud_stable_v100 folder, open .ipynb notebooks in Colab, and just follow the notebook instructions from there!
- please note: a Github account will be needed for authorisation. Go to Github and get one if you haven't >_<
For local execution:
git clone https://github.com/yc386/orthrus_metaproteomics.git
cd orthrus_metaproteomics/orthrus_local_runner
mamba env create -f environment.yaml
conda activate orthrus_metaproteomics
python walking_orthrus_locally_stable_v100.py --helpbasic usage
python walking_orthrus_locally_stable_v100.py --folder_path path_to_folder --file_type mgf --use_SwissProt \
--sage_path path_to_sage_binary --json_file_path path_to_sage_json \
--missed_cleavages 1 --max_variable_mods 2 \
--static_CAM --aas P N Q --mods 15.994915 0.984016 0.984016 \
--default_Percolator --joint_modellingFAQs
- Do I need a Google Colab subscription?
Without any Colab+, general CPU runtime, T4 GPU, and TPU should still be accessible. - Do I need a Google account?
May make life easier. Colab can also access files in your Google drive (with permission). - Help! Still unsure how to walk Orthrus.
Open an issue or get in touch with me (preprint)
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Jupyter Notebook90.2%Python9.8%
MIT License
Created November 15, 2024
Updated October 6, 2025
