SpecieScan: semi-automated taxonomic identification of bone collagen peptides from MALDI-ToF-MS
More On Article
- HEAS Keynote with Necmi Karul Takes Place in Vienna
- HEAS Members Publish Nature Communications Article with HEAS Speaker
- Ancient DNA reveals diverse community organizations in the 5th millennium BCE Carpathian Basin
- HEAS Member Awarded GO.INVESTIGATIO Fellowship by the Austrian Academy of Sciences
- A comparative archaeometric study of Late Bronze Age Black Lustrous and Red Lustrous Wheel-made wares from the Eastern Mediterranean
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).