MSLibrarian: Optimized Predicted Spectral Libraries for Data-Independent Acquisition Proteomics.

ABSTRACT: Data-independent acquisition-mass spectrometry (DIA-MS) is the method of choice for deep, consistent, and accurate single-shot profiling in bottom-up proteomics. While classic workflows for targeted quantification from DIA-MS data require auxiliary data-dependent acquisition (DDA) MS analysis of subject samples to derive prior-knowledge spectral libraries, library-free approaches based on in silico prediction promise deep DIA-MS profiling with reduced experimental effort and cost. Coverage and sensitivity in such analyses are however limited, in part, by the large library size and persistent deviations from the experimental data. We present MSLibrarian, a new workflow and tool to obtain optimized predicted spectral libraries by the integrated usage of spectrum-centric DIA data inter

SUBMITTER: Isaksson M 

PROVIDER: S-EPMC8822486 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature