Abstract
A key high-throughput proteomics technology to study proteins is mass spectrometryproteomics, whose data analysis involves the identification andquantification of proteins. In data-independent acquisition (DIA) modethe mass spectrometer systematically scans over a wide range ofmass-to-charge (m/z) values, resulting in more reproducible proteinabundances compared to other methods, making it a reliable method fordata analysis and comparison.To address the computational challenges associated with DIA dataanalysis, a workflow management tool Nextflow can be employed.Nextflow is particularly well-suited for proteomics data analysisworkflows, as it allows for the handling of complex and dynamicworkflows in a reproducible and scalable manner.In this context, we introduce glaDIAtor-nf, a free and open-sourceproteomics data analysis tool powered by Nextflow, which aims toassist researchers in the field of proteomics. To demonstrate itscapabilities, we showcase the performance of glaDIAtor-nf usingpublicly available datasets, including gold-standard spike-in datasetsand real-world biological datasets.