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DiaReport: Reproducible workflow for differential expression analysis and interactive reporting in DIA-based

Andrea Argentini^1,2, Esperanza Fernández^1,2, Jarne Pauwels^1,2

¹VIB-UGent Center for Medical Biotechnology, VIB, Ghent, B9052, Belgium.

Bioinformatics (Oxford, England)

|June 23, 2026

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DiaReport is a new R package for reproducible differential expression analysis of mass spectrometry proteomics data. It streamlines analysis and generates interactive reports for faster biological insights.

Area of Science:

Proteomics
Bioinformatics
Computational Biology

Background:

Data-independent acquisition (DIA) is a key mass spectrometry method in proteomics.
Reproducible workflows for differential expression (DE) analysis and reporting are limited.
Existing methods lack integrated solutions for DIA data analysis and visualization.

Purpose of the Study:

To introduce DiaReport, an R package for reproducible DE analysis of DIA proteomics data.
To provide a comprehensive tool for precursor and protein-level DE analysis.
To generate high-quality, interactive HTML reports for enhanced data interpretation.

Main Methods:

DiaReport integrates precursor data processing, missing value filtering, normalization, protein summarization, and statistical modeling.

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It utilizes MSqRob and QFeatures for DE analysis from DIA-NN output.

Interactive HTML reports are generated using Quarto, supporting various experimental designs.

Main Results:

DiaReport enables efficient analysis of DIA proteomics data, including precursor and protein levels.
The package ensures computational reproducibility through structured outputs and configuration files.
Application to an extracellular vesicle (EV) dataset demonstrated rapid insights into sample quality and protein differences.

Conclusions:

DiaReport offers a robust and reproducible solution for DIA proteomics data analysis.
The package facilitates rapid generation of insightful, interactive reports.
It supports diverse proteomic applications and experimental designs, enhancing data discoverability.