https://github.com/datajoint/element-calcium-imaging
DataJoint Element for multi-photon calcium imaging analysis with CaImAn, Suite2p, and EXTRACT
https://github.com/datajoint/element-calcium-imaging
Last synced: 3 months ago
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DataJoint Element for multi-photon calcium imaging analysis with CaImAn, Suite2p, and EXTRACT
- Host: GitHub
- URL: https://github.com/datajoint/element-calcium-imaging
- Owner: datajoint
- License: mit
- Created: 2020-12-09T13:43:12.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2025-02-14T16:45:31.000Z (4 months ago)
- Last Synced: 2025-03-30T02:03:38.768Z (3 months ago)
- Language: Jupyter Notebook
- Homepage: https://datajoint.com/docs
- Size: 17.5 MB
- Stars: 9
- Watchers: 13
- Forks: 47
- Open Issues: 14
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# DataJoint Element for Functional Calcium Imaging
DataJoint Element for functional calcium imaging with support for
[ScanImage](https://docs.scanimage.org/), [Scanbox](https://scanbox.org/), [Nikon
NIS-Elements](https://www.microscope.healthcare.nikon.com/products/software/nis-elements),
and `Bruker Prairie View` acquisition software; and
[Suite2p](https://github.com/MouseLand/suite2p),
[CaImAn](https://github.com/flatironinstitute/CaImAn), and
[EXTRACT](https://github.com/schnitzer-lab/EXTRACT-public) analysis software. DataJoint
Elements collectively standardize and automate data collection and analysis for
neuroscience experiments. Each Element is a modular pipeline for data storage and
processing with corresponding database tables that can be combined with other Elements
to assemble a fully functional pipeline. This repository also provides a tutorial
environment and notebooks to learn the pipeline.
## Experiment Flowchart
## Data Pipeline Diagram
### Legacy Support
+ Three variations of the pipeline were designed and supported through December 2024 to
handle different use cases. However, based on community feedback and use cases, only
one pipeline will be supported after December 2024. However, all three pipeline
versions will remain available in their own branches for reference and use.
+ Displayed above is the default `imaging` schema. Please see other branches for the
`imaging` module with `Curation` table and the `imaging_preprocess` module.
## Getting Started
+ Please fork this repository
+ Clone the repository to your computer
```bash
git clone https://github.com//element-calcium-imaging.git
```
+ Install with `pip`
```bash
pip install -e .
```
+ [Interactive tutorial on GitHub Codespaces](#interactive-tutorial)
+ [Documentation](https://datajoint.com/docs/elements/element-calcium-imaging)
## Support
+ If you need help getting started or run into any errors, please open a GitHub Issue
or contact our team by email at [email protected].
## Interactive Tutorial
+ The easiest way to learn about DataJoint Elements is to use the tutorial notebooks
within the included interactive environment configured using [Dev
Container](https://containers.dev/).
### Launch Environment
Here are some options that provide a great experience:
+ (*recommended*) Cloud-based Environment
+ Launch using [GitHub Codespaces](https://github.com/features/codespaces) using the
`+` option which will `Create codespace on main` in the codebase repository on your
fork with default options. For more control, see the `...` where you may create `New
with options...`.
+ Build time for a codespace is a few minutes. This is done infrequently and cached
for convenience.
+ Start time for a codespace is less than 1 minute. This will pull the built codespace
from cache when you need it.
+ *Tip*: Each month, GitHub renews a
[free-tier](https://docs.github.com/en/billing/managing-billing-for-github-codespaces/about-billing-for-github-codespaces#monthly-included-storage-and-core-hours-for-personal-accounts)
quota of compute and storage. Typically we run into the storage limits before
anything else since Codespaces consume storage while stopped. It is best to delete
Codespaces when not actively in use and recreate when needed. We'll soon be creating
prebuilds to avoid larger build times. Once any portion of your quota is reached,
you will need to wait for it to be reset at the end of your cycle or add billing
info to your GitHub account to handle overages.
+ *Tip*: GitHub auto names the codespace but you can rename the codespace so that it
is easier to identify later.
+ Local Environment
> *Note: Access to example data is currently limited to MacOS and Linux due to the
> s3fs utility. Windows users are recommended to use the above environment.*
+ Install [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
+ Install [Docker](https://docs.docker.com/get-docker/)
+ Install [VSCode](https://code.visualstudio.com/)
+ Install the VSCode [Dev Containers
extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers)
+ `git clone` the codebase repository and open it in VSCode
+ Use the `Dev Containers extension` to `Reopen in Container` (More info is in the
`Getting started` included with the extension.)
You will know your environment has finished loading once you either see a terminal open
related to `Running postStartCommand` with a final message of `Done` or the `README.md`
is opened in `Preview`.
Once the environment has launched, please run the following command in the terminal:
```sh
MYSQL_VER=8.0 docker compose -f docker-compose-db.yaml up --build -d
```
### Instructions
1. We recommend you start by navigating to the `notebooks` directory on the left panel
and go through the `tutorial.ipynb` Jupyter notebook. Execute the cells in the
notebook to begin your walk through of the tutorial.
2. Once you are done, see the options available to you in the menu in the bottom-left
corner. For example, in Codespace you will have an option to `Stop Current Codespace`
but when running Dev Container on your own machine the equivalent option is `Reopen
folder locally`. By default, GitHub will also automatically stop the Codespace after
30 minutes of inactivity. Once the Codespace is no longer being used, we recommend
deleting the Codespace.