Nipoppy: A framework for the reproducible organization and processing neuroimaging-clinical datasets

A Neurobagel complement project

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Nipoppy

Nipoppy is a lightweight framework for standardized organization and processing of datasets that have magnetic resonance imaging (MRI) and clinical data.

The framework consists of the following:

1. A data organization specification for both imaging and non-imaging data

   • Whenever possible, we follow the Brain Imaging Data Structure (BIDS) standard
   • We provide additional specifications for cases not (yet) covered by BIDS, such as phenotypic data and imaging derivatives

1. A standardized workflow process (i.e., protocol) covering the following:
   • Curation and organization of MRI and tabular data
     • E.g., conversion of DICOM data to BIDS
   • Standardized processing of imaging data using existing or custom pipelines
     • E.g., fMRIPrep, MRIQC
     • The Boutiques framework is used to flexibly execute and add new pipelines
   • Tracking of availability status for raw and processed data
     • We also develop an interactive dashboard for easy visualization of tracker results
   • Extraction of imaging-derived phenotypes (IDPs) into files ready for downstream analysis
2. A software package with tools to help work within the framework

Nipoppy can also provide metadata to Neurobagel tools to allow for data harmonization and federated search of participants across multiple studies.

People

Michelle Wang

PhD student

Nikhil Bhagwat

Academic Associate

Brent McPherson

Postdoctoral researcher

Remi Gau

Research Associate

Qing Wang (Vincent)

Postdoctoral researcher

Inés Gonzalez Pepe

Research Assistant