PT - JOURNAL ARTICLE AU - Jie Lisa Ji AU - Jure Demšar AU - Clara Fonteneau AU - Zailyn Tamayo AU - Lining Pan AU - Aleksij Kraljič AU - Andraž Matkovič AU - Nina Purg AU - Markus Helmer AU - Shaun Warrington AU - Michael Harms AU - Stamatios N. Sotiropoulos AU - John D. Murray AU - Alan Anticevic AU - Grega Repovš TI - QuNex – An Integrative Platform for Reproducible Neuroimaging Analytics AID - 10.1101/2022.06.03.494750 DP - 2022 Jan 01 TA - bioRxiv PG - 2022.06.03.494750 4099 - http://biorxiv.org/content/early/2022/06/05/2022.06.03.494750.short 4100 - http://biorxiv.org/content/early/2022/06/05/2022.06.03.494750.full AB - Neuroimaging technology has experienced explosive growth and has transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges around method integration (1–3). Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability. To address these challenges, we developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex is engineered for reproducible deployment of custom workflows, from onboarding raw data to generating analytic features, in a single “turnkey” command. The platform enables inter-operable integration of multi-modal, community-developed neuroimaging software through an extension frame-work with a software development kit for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia (4), including multiple clinical datasets. Moreover, QuNex enables integration of non-human primate, rodent, and human workflows via a cohesive translational platform. Collectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease.Competing Interest StatementJ.L.J. has previously worked for Neumora (formerly BlackThorn Therapeutics) and is a co-inventor on the following patent: Anticevic A, Murray JD, Ji JL: Systems and Methods for Neuro-Behavioral Relationships in Dimensional Geometric Embedding (N-BRIDGE), PCT International Application No. PCT/US2119/022110, filed March 13, 2019. C.F., A.K., and A.M have previously consulted for Neumora (formerly BlackThorn Therapeutics). J.D. and Z.T. have previously consulted for Neumora (formerly BlackThorn Therapeutics) and consult for Manifest Technologies. M.H. is an employee of Manifest Technologies. J.D.M. and A.A. consult for and hold equity with Neumora (formerly BlackThorn Therapeutics), Manifest Technologies, and are co-inventors on the following patents: Anticevic A, Murray JD, Ji JL: Systems and Methods for Neuro-Behavioral Relationships in Dimensional Geometric Embedding (N-BRIDGE), PCT International Application No. PCT/US2119/022110, filed March 13, 2019 and Murray JD, Anticevic A, Martin, WJ:Methods and tools for detecting, diagnosing, predicting, prognosticating, or treating a neurobehavioral phenotype in a subject, U.S. Application No. 16/149,903 filed on October 2, 2018, U.S. Application for PCT International Application No. 18/054,009 filed on October 2, 2018. G.R. consults for and holds equity with Neumora (formerly BlackThorn Therapeutics) and Manifest Technologies. The other authors report no competing interests.