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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
heifetslab_unravel-1.0.0b12.tar.gz
(404.8 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file heifetslab_unravel-1.0.0b12.tar.gz.
File metadata
- Download URL: heifetslab_unravel-1.0.0b12.tar.gz
- Upload date:
- Size: 404.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c7647548da3f11beaa1bdfae54636d69aaf19f26743781cf4d088d74a3562f54
|
|
| MD5 |
23b7b6f351b8f614fcb56c7f7b24a67e
|
|
| BLAKE2b-256 |
7ce7daabb80e030a67a6fb6eb763d2a9e4e750e5de32ad70c8c5d563bbecd101
|
File details
Details for the file heifetslab_unravel-1.0.0b12-py3-none-any.whl.
File metadata
- Download URL: heifetslab_unravel-1.0.0b12-py3-none-any.whl
- Upload date:
- Size: 599.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d11429846f021e5dfa88c9288f815bd3a1043f508553d4f9255c4d26ecf05c94
|
|
| MD5 |
2c2f2f75c8d17a0492ae39f79c2c9829
|
|
| BLAKE2b-256 |
e3d8fc3fbcc480abb6fd656de268967d96b4e7a2db89f330ad530e00667a9fc5
|
