Orthrus: an AI-powered, cloud-ready, and open-source hybrid approach for metaproteomics

preprint · bioRxiv · 2024

preprint · bioRxiv · 2024. Yun Chiang et al. While metaproteomics provides invaluable insight into microbial communities and functions, significant…
Date 2024-11-15
Type preprint
Venue bioRxiv
Publisher Cold Spring Harbor Laboratory
Contribution downstream-application
DOI 10.1101/2024.11.15.623814
Citations (OpenAlex) 5

Abstract

While metaproteomics provides invaluable insight into microbial communities and functions, significant bioinformatics challenges persist due to data complexity and the limitations of database searching. Orthrus is a hybrid approach combining transformer-based de novo sequencing with Casanovo and database searching with Sage plus Mokapot rescoring. Benchmarking against PEAKS 11, MaxQuant, and MetaNovo demonstrated high peptide outputs, taxonomic diversity, and proteome coverage. Orthrus is Python-based and accessible via Google Colaboratory.

Authors

  1. Yun Chiang · University of Copenhagen, Université Côte d’Azur
  2. Matthew James Collins · University of Cambridge, University of Copenhagen, University of York

Methods and tools

  • Orthrus: Open-source metaproteomics pipeline combining Casanovo transformer-based de novo sequencing with Sage database search and Mokapot rescoring.

Cites (3)

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