2026/06/30 by Charlotte Adams, Michael G. Leeming, David Teschner +3 · 1 voice
Decision Sciences · Chemistry · Medicine · #Scientific Computing and Data Management #Advanced Proteomics Techniques and Applications #Ethics in Clinical Research
paper · doi:10.1021/acs.jproteome.6c00265
Scientific confidence relies on the integrity and verifiability of primary observations, yet increasing experimental scales and computational complexities challenge traditional mechanisms of trust. In proteomics, community standards emphasize the public deposition of raw mass spectrometry (MS) data to enable reanalysis and reproducibility. However, recent advances in software capable of simulating MS data raise the possibility that datasets may be altered or generated entirely in silico and presented as experimentally acquired data. Here, we argue that current standards rarely distinguish between raw data formats in terms of their provenance guarantees or susceptibility to modification. To address this emerging vulnerability, we propose a hierarchy of evidence for MS-based reporting, analogous to established evidence hierarchies in medicine, in which confidence in reported findings increases with the traceability and verifiable provenance of raw data files. With this framework, we aim to support reviewers and readers in assessing the robustness of published claims and to stimulate discussion on strengthening data integrity safeguards in proteomics.