Bootstrapped Analysis of Stable Clusters- A semi-automated fMRI individual and group level functional parcellation technique
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README.md

PyBASC: Bootstrap Analysis of Stable Clusters in Python

PyBASC is an open , Nipype-based, parcellation package for preprocessed functional MRI data. Designed for use by both novice and expert users, PyBASC allows users to create individual and group level clustering solutions and compare the reliability and reproducibility of these clustering solutions across a wide variety of methods.

Core Dependencies

Python 3.6

Package Tested version
Scikit-learn 0.18.2
NumPy 1.13.1
NiBabel 2.1.0
SciPy 0.19.1
NiLearn 0.2.6
NiPype 0.13.1

Installation & Quick Start


  • Install from command line using pip
pip install PyBASC
  • Setup PyBASC from command line
cd /path/to/PyBASC
python setup.py install

Support

Please use GitHub issues for questions, bug reports or feature requests.

References

This package is based on the following work:

  • Garcia-Garcia, M., Nikolaidis, A., Bellec, P., Craddock, R. C., Cheung, B., Castellanos, F. X., & Milham, M. P. (2017). Detecting stable individual differences in the functional organization of the human basal ganglia. NeuroImage.
  • Bellec, P., Rosa-Neto, P., Lyttelton, O. C., Benali, H., & Evans, A. C. (2010). Multi-level bootstrap analysis of stable clusters in resting-state fMRI. Neuroimage, 51(3), 1126-1139.
  • Bellec, P., Marrelec, G., & Benali, H. (2008). A bootstrap test to investigate changes in brain connectivity for functional MRI. Statistica Sinica, 1253-1268.