STAVER: A Standardized Dataset-Based Algorithm for Efficient Variation Reduction in Large-Scale DIA MS Data

This project focuses on the development and application of STAVER, a standardized dataset-based algorithm designed to reduce variation in large-scale data-independent acquisition (DIA) mass spectrometry data. By using a reference dataset to standardize mass spectrometry signals, STAVER effectively reduces noise and enhances protein quantification accuracy, especially in the context of multi-library search. The effectiveness of STAVER is demonstrated in several large-scale DIA datasets, showing improved identification and quantification of thousands of proteins. The project aims to promote the adoption of multi-library search and improve the quality of DIA proteomics data through the open-source STAVER software package.