Achieving quantitative reproducibility in label-free multisite DIA experiments through multirun alignment.

ABSTRACT: DIA is a mainstream method for quantitative proteomics, but consistent quantification across multiple LC-MS/MS instruments remains a bottleneck in parallelizing data acquisition. One reason for this inconsistency and missing quantification is the retention time shift which current software does not adequately address for runs from multiple sites. We present multirun chromatogram alignment strategies to map peaks across columns, including the traditional reference-based Star method, and two novel approaches: MST and Progressive alignment. These reference-free strategies produce a quantitatively accurate data-matrix, even from heterogeneous multi-column studies. Progressive alignment also generates merged chromatograms from all runs which has not been previously achieved for LC-MS/MS data. F

SUBMITTER: Gupta S 

PROVIDER: S-EPMC10616189 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature