TY - JOUR
T1 - QuNex—An integrative platform for reproducible neuroimaging analytics
AU - Ji, Jie Lisa
AU - Demšar, Jure
AU - Fonteneau, Clara
AU - Tamayo, Zailyn
AU - Pan, Lining
AU - Kraljič, Aleksij
AU - Matkovič, Andraž
AU - Purg, Nina
AU - Helmer, Markus
AU - Warrington, Shaun
AU - Winkler, Anderson
AU - Zerbi, Valerio
AU - Coalson, Timothy S.
AU - Glasser, Matthew F.
AU - Harms, Michael P.
AU - Sotiropoulos, Stamatios N.
AU - Murray, John D.
AU - Anticevic, Alan
AU - Repovš, Grega
N1 - Publisher Copyright:
Copyright © 2023 Ji, Demšar, Fonteneau, Tamayo, Pan, Kraljič, Matkovič, Purg, Helmer, Warrington, Winkler, Zerbi, Coalson, Glasser, Harms, Sotiropoulos, Murray, Anticevic and Repovš.
PY - 2023
Y1 - 2023
N2 - Introduction: Neuroimaging technology has experienced explosive growth and 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 in method integration, particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability. Methods: To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a “turnkey” command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features. Results: The platform enables interoperable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) 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, including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform. Discussion: 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.
AB - Introduction: Neuroimaging technology has experienced explosive growth and 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 in method integration, particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability. Methods: To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a “turnkey” command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features. Results: The platform enables interoperable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) 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, including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform. Discussion: 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.
KW - cloud integration
KW - containerization
KW - data processing
KW - diffusion MRI
KW - functional MRI
KW - high-performance computing
KW - multi-modal analyses
KW - neuroimaging
UR - http://www.scopus.com/inward/record.url?scp=85153092452&partnerID=8YFLogxK
U2 - 10.3389/fninf.2023.1104508
DO - 10.3389/fninf.2023.1104508
M3 - Article
C2 - 37090033
AN - SCOPUS:85153092452
SN - 1662-5196
VL - 17
JO - Frontiers in Neuroinformatics
JF - Frontiers in Neuroinformatics
M1 - 1104508
ER -