DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools

Area of Science:

• Proteomics
• Mass Spectrometry
• Bioinformatics

Background:

• Data-Independent Acquisition (DIA) is a crucial technique in proteomics for large-scale protein quantification.
• Benchmarking software tools for DIA analysis is essential for reliable and reproducible results.
• A comprehensive, standardized reference dataset is needed to evaluate DIA software performance.

Purpose of the Study:

• To generate and provide a large-scale, high-quality proteomic reference dataset for benchmarking DIA analysis software.
• To facilitate the assessment of various DIA software tools using a standardized experimental setup.
• To support the development and improvement of bioinformatics tools for proteomics data analysis.

Main Methods:

• Acquisition of 96 DIA raw files from a complex proteomic standard (E.coli background spiked with UPS1 Sigma proteins) using an Orbitrap mass spectrometer.
• Analysis using 4 different DIA window schemes and triplicates for 8 different protein concentrations.
• Inclusion of spectral libraries, FASTA files, software outputs from six DIA tools, and post-processed quantification tables.

Main Results:

• Generation of the most comprehensive DIA reference dataset acquired on an Orbitrap instrument to date.
• Dataset includes raw files, spectral libraries, FASTA files, software outputs, and processed quantification tables.
• All data made available on ProteomeXchange for broad accessibility.

Conclusions:

• The provided dataset serves as a valuable resource for the proteomics community.
• It enables rigorous benchmarking of DIA software tools and validation of analysis pipelines.
• Facilitates training for students and aids developers in enhancing DIA analysis software.