https://github.com/datajoint/workflow-zstack

Example DataJoint workflow for volumetric data analysis using BossDB
https://github.com/datajoint/workflow-zstack

Last synced: 4 months ago
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Example DataJoint workflow for volumetric data analysis using BossDB

• Host: GitHub
• URL: https://github.com/datajoint/workflow-zstack
• Owner: datajoint
• License: mit
• Created: 2023-02-22T15:03:01.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-03T14:03:12.000Z (over 1 year ago)
• Last Synced: 2025-01-10T16:23:07.131Z (6 months ago)
• Language: Jupyter Notebook
• Homepage: https://datajoint.com/docs
• Size: 121 KB
• Stars: 0
• Watchers: 8
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# DataJoint Workflow for ZStack Imaging

The DataJoint Workflow for ZStack Imaging combines five DataJoint Elements for

volume cell segmentation - Elements Lab, Animal, Session, Calcium Imaging, and

ZStack. 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 notebook to learn the pipeline.

## Experiment Flowchart

![flowchart](https://raw.githubusercontent.com/datajoint/element-zstack/main/images/flowchart.svg)

## Data Pipeline Diagram

![pipeline](https://raw.githubusercontent.com/datajoint/element-zstack/main/images/pipeline.svg)

## Getting Started

+ [Interactive tutorial](#interactive-tutorial)

+ Install Element ZStack from PyPI

     ```bash

     pip install element-zstack

     ```

+ [Documentation](https://datajoint.com/docs/elements/element-zstack)

## Support

+ If you need help getting started or run into any errors, please contact our team by email at [email protected].

## Interactive Tutorial

### Launch Environment

+ Local Environment

  + Install [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)

  + Install [VSCode](https://code.visualstudio.com/)

  + Install [Conda](https://docs.conda.io/en/latest/miniconda.html)

  + Configure a database.  See [here](https://tutorials.datajoint.org/setting-up/local-database.html) for details.

  + `git clone` the code repository and open it in VSCode

  + Install the repository with `pip install -e .`

  + Setup a `dj_local_conf.json` with the `database.prefix` and `volume_root_data_dir`. See [User Guide](https://datajoint.com/docs/elements/user-guide/) for details.

  + Add your example data to the `volume_root_data_dir`.

### Instructions

1. To upload data to BossDB, [create an account](https://api.bossdb.io) to

   access the BossDB API and generate an API token. Please contact the team at [BossDB](https://bossdb.org)

   to ensure you have `resource-manager` permissions for your account. 

2. Follow the instructions below to set up the

   [intern](https://github.com/jhuapl-boss/intern) REST API locally. 

   + Create a new folder `.intern` in your user directory.

   + Create a configuration file `intern.cfg` within the `.intern` folder. The

     path to this file should be `~/.intern/intern.cfg`. 

   + The `intern.cfg` file should contain the following exactly as shown below:

   ```bash

    # ~/.intern/intern.cfg

    [Default]

    protocol = https

    host = api.bossdb.io

    token = 

   ```

3. Use the instructions above to set up a local environment.

4. Navigate to the `notebooks` directory. Execute the cells in the notebooks to begin your walk through of the tutorial.