Neuroscience data analysis framework for reproducible research
Project description
spyglass
spyglass is a data analysis framework that facilitates the storage, analysis, visualization, and sharing of neuroscience data to support reproducible research. It is designed to be interoperable with the NWB format and integrates open-source tools into a coherent framework.
Documentation can be found at - https://lorenfranklab.github.io/spyglass/
Installing from pip
Install spyglass
pip install spyglass-neuro
Some functions may take advantage of the latest changes to spike interface, which currently has a slow release cycle. To get the latest changes:
pip install git+https://github.com/SpikeInterface/spikeinterface.git
The Frank Lab typically uses mountainsort, although spyglass uses spikeinterface, which allows for any spike sorter. To install mountainsort:
pip install mountainsort4
Spyglass uses the package ghostipy for filtering of signals:
pip install ghostipy
WARNING: If you are on an M1 Mac, you need to install pyfftw via conda BEFORE installing ghostipy
conda install -c conda-forge pyfftw
Finally, if you want to decode on the GPU, you must install cupy:
conda install -c conda-forge cupy
Setup
See the documentation for setup instructions - https://lorenfranklab.github.io/spyglass/type/html/installation.html
Tutorials
The tutorials for spyglass is currently in the form of Jupyter Notebooks and can be found in the notebooks directory. We strongly recommend opening them in the context of jupyterlab.
Contributing
See the Developer's Note for contributing instructions found at - https://lorenfranklab.github.io/spyglass/type/html/how_to_contribute.html
License/Copyright
License and Copyright notice can be found at https://lorenfranklab.github.io/spyglass/type/html/copyright.html
Citation
Kyu Hyun Lee, Eric Denovellis, Ryan Ly, Jeremy Magland, Jeff Soules, Alison Comrie, Jennifer Guidera, Rhino Nevers, Daniel Gramling, Philip Adenekan, Ji Hyun Bak, Emily Monroe, Andrew Tritt, Oliver Rübel, Thinh Nguyen, Dimitri Yatsenko, Joshua Chu, Caleb Kemere, Samuel Garcia, Alessio Buccino, Emily Aery Jones, Lisa Giocomo, and Loren Frank. Spyglass: A Data Analysis Framework for Reproducible and Shareable Neuroscience Research. Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2022.
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