A graph-based approach for modification site assignment in proteomics
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866915301037178880 |
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| author | Skiadopoulou, Dafni Käll, Lukas Barsnes, Harald Schwämmle, Veit Vaudel, Marc |
| author_facet | Skiadopoulou, Dafni Käll, Lukas Barsnes, Harald Schwämmle, Veit Vaudel, Marc |
| contents | Background In proteomics, the most probable localizations of post-translational modifications are assessed by localization scores evaluating the likelihood of a given modification to occupy a site on a peptide sequence. When identifying highly modified peptides, localization scores for different modifications can return conflicting results, stacking modifications on the same amino acid. Here, we propose a graph-based approach that assigns modifications to sites in a way that maximizes localization scores while avoiding conflicting assignments. Results The algorithm is implemented as both a standalone Python program and in the compomics-utilities Java library. Our graph-based approach showed the ability to match complex combinations of modifications and acceptor sites, allowing the processing of thousands of peptides in a few seconds. Conclusions Our graph-based approach to modification site assignment allows distributing multiple modifications in a way that maximizes individual localization scores. Having an optimal modification site assignment is important for spectrum annotation and biological interpretation. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_17755 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A graph-based approach for modification site assignment in proteomics Skiadopoulou, Dafni Käll, Lukas Barsnes, Harald Schwämmle, Veit Vaudel, Marc Quantitative Methods Background In proteomics, the most probable localizations of post-translational modifications are assessed by localization scores evaluating the likelihood of a given modification to occupy a site on a peptide sequence. When identifying highly modified peptides, localization scores for different modifications can return conflicting results, stacking modifications on the same amino acid. Here, we propose a graph-based approach that assigns modifications to sites in a way that maximizes localization scores while avoiding conflicting assignments. Results The algorithm is implemented as both a standalone Python program and in the compomics-utilities Java library. Our graph-based approach showed the ability to match complex combinations of modifications and acceptor sites, allowing the processing of thousands of peptides in a few seconds. Conclusions Our graph-based approach to modification site assignment allows distributing multiple modifications in a way that maximizes individual localization scores. Having an optimal modification site assignment is important for spectrum annotation and biological interpretation. |
| title | A graph-based approach for modification site assignment in proteomics |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2505.17755 |