Academic Journal
PEPerMINT: peptide abundance imputation in mass spectrometry-based proteomics using graph neural networks
| العنوان: | PEPerMINT: peptide abundance imputation in mass spectrometry-based proteomics using graph neural networks |
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| المؤلفون: | Pietz, Tobias, Gupta, Sukrit, Schlaffner, Christoph N., Ahmed, Saima, Steen, Hanno, Renard, Bernhard Y., Baum, Katharina |
| سنة النشر: | 2024 |
| المجموعة: | FU Berlin: Refubium |
| مصطلحات موضوعية: | peptide abundance imputation, mass spectrometry-based proteomics, graph neural networks, ddc:570 |
| الوصف: | Motivation Accurate quantitative information about protein abundance is crucial for understanding a biological system and its dynamics. Protein abundance is commonly estimated using label-free, bottom-up mass spectrometry (MS) protocols. Here, proteins are digested into peptides before quantification via MS. However, missing peptide abundance values, which can make up more than 50% of all abundance values, are a common issue. They result in missing protein abundance values, which then hinder accurate and reliable downstream analyses. Results To impute missing abundance values, we propose PEPerMINT, a graph neural network model working directly on the peptide level that flexibly takes both peptide-to-protein relationships in a graph format as well as amino acid sequence information into account. We benchmark our method against 11 common imputation methods on 6 diverse datasets, including cell lines, tissue, and plasma samples. We observe that PEPerMINT consistently outperforms other imputation methods. Its prediction performance remains high for varying degrees of missingness, different evaluation approaches, and differential expression prediction. As an additional novel feature, PEPerMINT provides meaningful uncertainty estimates and allows for tailoring imputation to the user’s needs based on the reliability of imputed values. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | 9 Seiten; application/pdf |
| اللغة: | English |
| DOI: | 10.17169/refubium-45080 |
| DOI: | 10.1093/bioinformatics/btae389 |
| الاتاحة: | https://refubium.fu-berlin.de/handle/fub188/45368 https://doi.org/10.17169/refubium-45080 https://doi.org/10.1093/bioinformatics/btae389 |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.E1B86EFB |
| قاعدة البيانات: | BASE |
| DOI: | 10.17169/refubium-45080 |
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