In-depth analysis of data characteristics and comparative evaluation of dda and dia accuracy in label-free quantitative proteomics of biological samples.

ABSTRACT: Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA) are widely used in MS-based proteomics. However, a comprehensive evaluation of their data characteristics-including protein and peptide identification, differential expression analysis, and the performance in revealing biological insights-remains lacking. In this study, we conducted a systematic comparison of DDA and DIA across three model sample types: one disease model, two drug-treated models, and their respective controls. Our analysis extended beyond conventional metrics such as total protein and peptide counts, precision, and accuracy, to include data completeness, detection of positive control markers, reproducibility, functional annotation reliability, and sources of methodological variation. The results demons

SUBMITTER: Zou X 

PROVIDER: S-EPMC12801617 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature