dipy_buan_profiles

Synopsis

Workflow of bundle analytics.

Applies statistical analysis on bundles of subjects and saves the results in a directory specified by out_dir. Supports two modes auto-detected from the directory structure: - Group mode: subject_folder contains patient/ and control/ subdirectories, each with per-subject subdirectories containing rec_bundles/, org_bundles/, and anatomical_measures/. Outputs HDF5 files suitable for linear mixed model analysis. - Single-subject mode: subject_folder directly contains rec_bundles/, org_bundles/, and anatomical_measures/ (or the paths are overridden via bundle_folder, orig_bundle_folder, and metric_folder). Outputs .npy profile arrays (one per bundle/metric pair). See [1] for further details about the method.

Usage

dipy_buan_profiles [OPTIONS] model_bundle_folder subject_folder

Input Parameters

• model_bundle_folder

  Path to the input model bundle files. This path may contain wildcards to process multiple inputs at once.

• subject_folder

  Path to the subject folder. Either a group-level directory (containing patient/ and control/ subdirs) or a single-subject directory (directly containing rec_bundles/, org_bundles/, and anatomical_measures/).

General Options

• --bundle_folder

  Override path for the registered bundles in common space (replaces <subject_folder>/rec_bundles). Only used in single-subject mode. (default: None)

• --orig_bundle_folder

  Override path for the bundles in native space (replaces <subject_folder>/org_bundles). Only used in single-subject mode. (default: None)

• --metric_folder

  Override path for the metric files (replaces <subject_folder>/anatomical_measures). Only used in single-subject mode. (default: None)

• --no_disks

  Number of disks used for dividing bundle into disks. (default: 100)

Output Options

• --out_dir

  Output directory. (default: current directory)

References

[1]

Bramsh Qamar Chandio, Shannon Leigh Risacher, Franco Pestilli, Daniel Bullock, Fang-Cheng Yeh, Serge Koudoro, Ariel Rokem, Jaroslaw Harezlak, and Eleftherios Garyfallidis. Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations. Scientific Reports, 10:17149, October 2020. URL: https://doi.org/10.1038/s41598-020-74054-4, doi:10.1038/s41598-020-74054-4.

Garyfallidis, E., M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, and I. Nimmo-Smith. Dipy, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, 1-18, 2014.