SpecieScan: semi-automated taxonomic identification of bone collagen peptides from MALDI-ToF-MS
More On Article
- HEAS Member Discusses Tischoferhöhle on Austrian National Television
- HEAS Seed Grants June 2025 Round
- Decoding genomic landscapes of introgression.
- New insights from the application of ZooMS to Late Pleistocene fauna from Grotta di Castelcivita, southern Italy
- Exploring Ancient Foodways - An archaeological journey into Roman dietary habits at Kinderuni Wien 2025
Végh, E.I., Douka, K., 2024. SpecieScan: semi-automated taxonomic identification of bone collagen peptides from MALDI-ToF-MS. Bioinformatics 40.
Abstract
Motivation
Zooarchaeology by Mass Spectrometry (ZooMS) is a palaeoproteomics method for the taxonomic determination of collagen, which traditionally involves challenging manual spectra analysis with limitations in quantitative results. As the ZooMS reference database expands, a faster and reproducible identification tool is necessary. Here we present SpecieScan, an open-access algorithm for automating taxa identification from raw MALDI-ToF mass spectrometry (MS) data.
Results
SpecieScan was developed using R (pre-processing) and Python (automation). The algorithm’s output includes identified peptide markers, closest matching taxonomic group (taxon, family, order), correlation scores with the reference databases, and contaminant peaks present in the spectra. Testing on original MS data from bones discovered at Palaeothic archaeological sites, including Denisova Cave in Russia, as well as using publicly-available, externally produced data, we achieved >90% accuracy at the genus-level and ∼92% accuracy at the family-level for mammalian bone collagen previously analysed manually.
Availability and implementation
The SpecieScan algorithm, along with the raw data used in testing, results, reference database, and common contaminants lists are freely available on Github (https://github.com/mesve/SpecieScan).