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compareMS2 is a tool for direct comparison of tandem mass spectrometry (MS/MS) datasets, typically from LC-MS/MS, in proteomics or metabolomics, defining a distance as a function of the share of similar spectra. Applications span biomedicine, phylogenetics, forensics, ecology and food science.
compareMS2 calculates the similarity between tandem mass spectrometry datasets and visualizes the results in a phylogenetic tree.
In a 2019 paleoproteomic study (Horn et al., Zool J Linn Soc 186:3, pp. 650–665), compareMS2 was critical for turning complex MS/MS data from ancient and modern bird bones into reliable taxonomic evidence. By enabling robust comparison of peptide spectra across specimens and extractions, it supported confident identification of COL1A1/COL1A2 sequence variation and helped place the dodo, great auk and other birds in phylogenetically meaningful clades, complementing DNA-based classification.
CompareMS2 is a valuable tool with considerable potential for comparing proteomic datasets from non-model organisms. It has been invaluable for our species identification work on fur. It enables direct, transparent comparison of MS/MS spectra, helping distinguish homologous peptide markers across closely related taxa and degraded forensic samples. Its ability to support peptide-level evidence makes it an important tool for translating protein mass spectrometry data into species identifications.
The compareMS2 software provides a surprisingly simple and intuitive framework for comparing tandem mass spectra, regardless of their origin. For example, we used it to compare meat and meat products from a range of mammalian species in the wake of the horse meat scandal. This work was also reported in a major newspaper. The "spectral matching" approach is very simple, and does not need any other data than the mass spectra themselves.
I use CompareMS2 as a framework to assess spectral similarity between mass spec datasets using reference samples. Because the approach is based on spectral distance rather than predefined labels, it is easy to tweak to different experimental settings, instrument platforms, or sample types. In particular it is useful for retrospective metadata extraction and validation.
CLIMESEAFOOD models climate-driven changes in marine food webs and contaminant bioaccumulation, improves understanding of trophic transfer and seafood safety, assesses high-latitude ecosystem responses, and evaluates future seafood risks under climate and fisheries scenarios.