Authors
Demsar, J., Kraljic, A., Matkovic, A., Brege, S., Pan, L., Tamayo, Z., Fonteneau, C., Helmer, M., Ji, J. L., Anticevic, A., Korponay, C., Salavrakos, M., Glasser, M. F., Nickerson, L. D., Cho, Y. T., Repovs, G.
Abstract
Preprocessing and analysis of neuroimaging data are technically demanding, often requiring a combination of multiple software tools, modality-specific pipelines, and extensive parameter tuning to match dataset characteristics. These complexities make it difficult to document workflows in sufficient detail to ensure complete transparency and reproducibility. To address these challenges, we introduce QuNex recipes, a framework for defining and executing complete neuroimaging workflows -- encompassing data onboarding, preprocessing, and analysis -- in a transparent, machine- and human-readable format. Recipes are implemented as an integrated feature of the Quantitative Neuroimaging Environment & Toolbox (QuNex), a containerized, open-source platform for end-to-end multimodal and multi-species neuroimaging processing. The recipes framework enables seamless integration of QuNex commands with custom scripts and external tools, capturing every processing step and parameter setting. A fully reproducible study can thus be shared and replicated by providing only (a) the QuNex version used, (b) the recipe file, and (c) the data. This approach standardizes workflow specification, enhances transparency, and enables one-command replication of complex neuroimaging analyses. By providing a standardized way to describe and share workflows, recipes facilitate open exchange of best practices and reproducible methods within the neuroimaging community.
Preprint server:
bioRxiv
The authors list and abstract were imported from bioRxiv on 11 Nov 2025.
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