Pre-analytical Sample Quality Determines Performance of Plasma Proteomics Workflows for Biomarker Discovery

This dataset contains mass spectrometry-based proteomic analyses of human plasma samples processed through five distinct proteomics workflows: neat plasma, perchloric acid precipitation with neutralization (PCA-N), and three bead-based enrichment methods (SAX magnetic beads, Sera Sil 700 magnetic beads, and non-magnetic beads). The study systematically evaluates how sample quality affects proteome coverage and quantification performance across these workflows through controlled spike-in experiments. We performed spike-in series of platelets, erythrocytes, and peripheral blood mononuclear cells (PBMCs) to assess workflow-specific susceptibilities to cellular contamination. Additional experiments include yeast protein spike-ins to evaluate detection of low-abundance proteins, buffer-bead combination screening, freeze-thaw cycle effects, and centrifugation condition comparisons. The dataset provides comprehensive evidence for how pre-analytical variables impact plasma proteome characterization and establishes quantitative benchmarks for assessing plasma sample quality in biomarker discovery studies.