STAVER: a standardized benchmark dataset-based algorithm for effective variation reduction in large-scale DIA-MS data.

ABSTRACT: Mass spectrometry (MS)-based proteomics has become instrumental in comprehensively investigating complex biological systems. Data-independent acquisition (DIA)-MS, utilizing hybrid spectral library search strategies, allows for the simultaneous quantification of thousands of proteins, showing promise in enhancing protein identification and quantification precision. However, low-quality profiles can considerably undermine quantitative precision, resulting in inaccurate protein quantification. To tackle this challenge, we introduced STAVER, a novel algorithm that leverages standardized benchmark datasets to reduce non-biological variation in large-scale DIA-MS analyses. By eliminating unwanted noise in MS signals, STAVER significantly improved protein quantification precision, especially in

SUBMITTER: Ran P 

PROVIDER: S-EPMC11540132 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature