MassIVE.quant: a community resource of quantitative mass spectrometry-based proteomics datasets

Area of Science:

• Proteomics
• Biotechnology
• Data Science

Background:

• Quantitative mass spectrometry-based proteomics generates large, complex datasets.
• Reproducibility is a major challenge in computational proteomics.
• Standardized data repositories are needed to facilitate data sharing and validation.

Purpose of the Study:

• To introduce MassIVE.quant, a novel repository infrastructure for reproducible quantitative proteomics.
• To ensure compatibility with diverse mass spectrometry data and analysis tools.
• To establish a systematic approach for storing all components of a proteomics study.

Main Methods:

• Development of a repository infrastructure named MassIVE.quant.
• Implementation of a branch structure for systematic data storage.
• Ensuring compatibility with all mass spectrometry data acquisition types and computational analysis tools.

Main Results:

• MassIVE.quant supports reproducible quantitative mass spectrometry-based proteomics.
• The repository infrastructure is compatible with all mass spectrometry data acquisition types and computational analysis tools.
• A branch structure allows systematic storage of raw data, metadata, analysis scripts, and intermediate files.

Conclusions:

• MassIVE.quant enhances the reproducibility of quantitative proteomics studies.
• The resource facilitates systematic data management and reanalysis.
• It serves as a valuable data resource for the proteomics community.