UNRAVEL: UN-biased high-Resolution Analysis and Validation of Ensembles using Light sheet images
Project description
UN-biased high-Resolution Analysis and Validation of Ensembles using Light sheet images
- UNRAVEL is a Python package & command line tool for the analysis of brain-wide imaging data, automating:
- Registration of brain-wide images to a common atlas space
- Quantification of cell/label densities across the brain
- Voxel-wise analysis of fluorescent signals and cluster correction
- Validation of hot/cold spots via cell/label density quantification at cellular resolution
- UNRAVEL can be installed via PyPI:
pip install heifetslab-unravel - Initial UNRAVEL publication
- UNRAVEL was developed by the Heifets lab and TensorAnalytics
- Additional support/guidance was provided by:
Please see UNRAVEL documentation for guides on installation and analysis
UNRAVEL visualizer
- UNRAVEL visualizer is a web-based tool for visualizing and exploring 3D maps output from UNRAVEL
- UNRAVEL visualizer GitHub repo
- Developed by MetaCell with support from the Heifets lab
Contact us
If you have any questions, suggestions, or are interested in collaborations and contributions, please reach out to us.
Developers
- Daniel Ryskamp Rijsketic (developer and maintainer) - danrijs@stanford.edu
- Austen Casey (developer) - abcasey@stanford.edu
- MetaCell (UNRAVEL visualizer developers) - info@metacell.us
- Boris Heifets (PI) - bheifets@stanford.edu
Additional contributions from
- Mehrdad Shamloo (PI) - shamloo@stanford.edu
- Daniel Barbosa (early contributer and guidance) - Dbarbosa@pennmedicine.upenn.edu
- Wesley Zhao (guidance) - weszhao@stanford.edu
- Nick Gregory (guidance) - ngregory@stanford.edu
Main dependencies
- Allen Institute for Brain Science
- FSL
- fslpy
- ANTsPy
- Ilastik
- nibabel
- numpy
- scipy
- pandas
- cc3d
- Registration and warping workflows were inspired by MIRACL
- We warped this LSFM/iDISCO+ average template brain to Allen brain atlas space (CCFv3) and refined alignment.
Support is welcome for
- Analysis of new datasets
- Development of new features
- Maintenance of the codebase
- Guidance of new users
Release history Release notifications | RSS feed
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