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Proteomics experiments rely on complex, multistep workflows that include sample solubilization, protein digestion, cysteine reduction and alkylation, peptide separation by reversed-phase nanoliquid chromatography, tandem mass spectrometry, spectral matching, and data processing. Ensuring consistent performance is critical, as variability at any stage can compromise data quality. Although extensive methodologies and software exist to monitor instrument performance, overall workflow evaluation is often limited to coarse metrics such as the total number of proteins, peptides, and/or peptide spectral matches. To address this limitation, the Proteomics Visualization and Evaluation Tool (Pro-VET), a software platform that provides comprehensive metrics for assessing proteomics workflow performance, was developed. Pro-VET is implemented in Python and distributed as a standalone Windows executable. The software enables comparison of a wide range of peptide properties, including hydrophobicity, missed cleavages, amino acid composition, and peptide length. In addition, Pro-VET supports visualization of any of 566 peptide properties derived from the AAindex database. A novel quantitative metric, similarity index, which enables direct comparison of proteomics runs, is also introduced. It compares the peptides detected from the more abundant proteins. Pro-VET outputs both figures and raw data files, facilitating downstream visualization and analysis. The utility of Pro-VET is demonstrated using three representative case studies.
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David M. Smalley (2026) studied this question.
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