MOTIVATION: High-throughput omics technologies generate complex datasets with thousands of features that are quantified across multiple experimental conditions, but often suffer from incomplete measurements, missing values, and individually fluctuating variances. This requires analytical tools for accurate, deep and insightful biological interpretation, capable of dealing with a large variety of data properties and different amounts of completeness. Software capable of handling such data complexity and integrating with external applications for downstream analysis remains rare and mostly relies on programming-based environments, limiting accessibility for researchers without computational expertise. RESULTS: We present OmicsQ, an interactive, web-based platform designed to streamline quantitative omics data analysis. OmicsQ provides an intuitive, browser-based visualization interface that integrates established statistical processing tools. Those include robust batch correction, automated experimental design annotation, and handling of missing data without imputation, which maintains data integrity and avoids artifacts from a priori assumptions. OmicsQ seamlessly interacts with external applications (e.g. PolySTest, VSClust, ComplexBrowser) for statistical testing, clustering, analysis of protein complex behavior, and pathway enrichment, offering a comprehensive and flexible workflow from data import to biological interpretation that is broadly applicable across domains. AVAILABILITY AND IMPLEMENTATION: OmicsQ is implemented in R and Shiny and is available at https://computproteomics.bmb.sdu.dk/app_direct/OmicsQ. Source code and installation instructions: https://github.com/computproteomics/OmicsQ, DOI: 10.5281/zenodo.17778420.

MOTIVATION: The proteomics field requires the production and publication of reliable mass spectrometry-based identification and quantification results. Although many tools or algorithms exist, very few consider the importance of combining, in a unique software environment, efficient processing algorithms and a data management system to process and curate hundreds of datasets associated with a single proteomics study. RESULTS: Here, we present Proline, a robust software suite for analysis of MS-based proteomics data, which collects, processes and allows visualization and publication of proteomics datasets. We illustrate its ease of use for various steps in the validation and quantification workflow, its data curation capabilities and its computational efficiency. The DDA label-free quantification workflow efficiency was assessed by comparing results obtained with Proline to those obtained with a widely used software using a spiked-in sample. This assessment demonstrated Proline's ability to provide high quantification accuracy in a user-friendly interface for datasets of any size. AVAILABILITY AND IMPLEMENTATION: Proline is available for Windows and Linux under CECILL open-source license. It can be deployed in client-server mode or in standalone mode at http://proline.profiproteomics.fr/#downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: With the advent of fully automated sample preparation robots for Hydrogen-Deuterium eXchange coupled to Mass Spectrometry (HDX-MS), this method has become paramount for ligand binding or epitope mapping screening, both in academic research and biopharmaceutical industries. However, bridging the gap between commercial HDX-MS software (for raw data interpretation) and molecular viewers (to map experiment results onto a 3D structure for biological interpretation) remains laborious and requires simple but sometimes limiting coding skills. We solved this bottleneck by developing HDX-Viewer, an open-source web-based application that facilitates and quickens HDX-MS data analysis. This user-friendly application automatically incorporates HDX-MS data from a custom template or commercial HDX-MS software in PDB files, and uploads them to an online 3D molecular viewer, thereby facilitating their visualization and biological interpretation. AVAILABILITY AND IMPLEMENTATION: The HDX-Viewer web application is released under the CeCILL (http://www.cecill.info) and GNU LGPL licenses and can be found at https://masstools.ipbs.fr/hdx-viewer. The source code is available at https://github.com/david-bouyssie/hdx-viewer.