MaxDIA enables library-based and library-free data-independent acquisition proteomics

Area of Science:

• Proteomics
• Computational Biology
• Biochemistry

Background:

• Data-independent acquisition (DIA) proteomics is crucial for deep proteome coverage.
• Accurate quantification and false discovery rate (FDR) control are essential for reliable DIA analysis.
• Existing software may have limitations in proteome coverage and quantification accuracy.

Purpose of the Study:

• To introduce MaxDIA, a novel software platform for analyzing DIA proteomics data.
• To improve proteome coverage and quantification accuracy in DIA experiments.
• To provide reliable FDR control for both library-based and hypothesis-free DIA analysis.

Main Methods:

• MaxDIA utilizes spectral libraries for enhanced proteome coverage and quantification.
• Employs three- or four-dimensional feature detection and machine learning for match scoring.
• Incorporates a bootstrap DIA workflow for iterative recalibration and stringent matching.
• Integrates with BoxCar acquisition and trapped ion mobility spectrometry.

Main Results:

• MaxDIA achieves deep proteome coverage with superior coefficients of variation compared to other software.
• Provides accurate FDR estimates at both library-to-DIA match and protein levels.
• Enables hypothesis-free discovery DIA analysis with reliable FDR control.
• Combined with new technologies, MaxDIA leads to deep and accurate proteome quantification.

Conclusions:

• MaxDIA is a powerful software platform for advanced DIA proteomics data analysis.
• It significantly improves proteome coverage, quantification accuracy, and FDR control.
• MaxDIA facilitates both library-based and discovery-oriented DIA workflows, advancing proteomic research.