FluoPi
Code and teaching materials for UC/BackyardBrains raspberry pi "macro" scope.
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
○codemeta.json file
-
○.zenodo.json file
-
✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: biorxiv.org, plos.org -
○Committers with academic emails
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (12.4%) to scientific vocabulary
Last synced: 11 months ago
·
JSON representation
Repository
Code and teaching materials for UC/BackyardBrains raspberry pi "macro" scope.
Basic Info
Statistics
- Stars: 26
- Watchers: 6
- Forks: 16
- Open Issues: 5
- Releases: 0
Created over 9 years ago
· Last pushed over 2 years ago
https://github.com/RudgeLab/FluoPi/blob/master/
# [][website] Hardware design files, code and teaching materials for a low cost and open source fluorescent image registration station. ## Overview FluoPi is composed of a blue-light transilluminator, an amber acrylic filter and a raspberry camera contained in a black acrylic mainframe. All the hardware is controlled with a Raspberry pi small computer. With this equipment you are able to: * Take images of fluorescent samples ranges from um to cm. * Perform timelapse assays of up to 3 fluorescent proteins simultaneously * See electrophoresis gel stained with blue excitable chemicals (such as GelRed or SYBR Safe). ## Getting Started You can see the full project at [OSF](https://osf.io/dy6p2/) and a pre-print manuscript at [Biorxiv](https://www.biorxiv.org/content/early/2017/09/27/194324) and peer-reviewed article in [PLoS](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187163) ### Prerequisites To assemble this device you need access to a laser cutter and a 3D printer. You also need a mouse, keyboard and a screen with HDMI (or hdmi to VGA adaptor) to connect with the Raspberry pi (you can also manage the equipment through SSH or using programs such as [teamviewer](https://pages.teamviewer.com/published/raspberrypi/)) ### Installing All the installation instructions are available on the [wiki page][wiki] Full documentation and assembly instructions can be found at [Docubricks](http://docubricks.com/viewer.jsp?id=701517893260717056) ### Running the equipment The equipment has a manual switch and the camera can be controlled with [_camera module commands_](https://www.raspberrypi.org/documentation/usage/camera/raspicam/README.md). The project includes some python codes (based on [camera python module](https://www.raspberrypi.org/documentation/usage/camera/python/)) to control the hardware: * _timelapse.py_ --> to perform timelapse experiments * _turnON.py_ --> to turn ON the transilluminator * _turnOFF.py_ --> to turn OFF the transilluminator ### Running the notebooks Jupyter notebooks are included (Examples/ and Tutorials/) to demonstrate the analysis principles and the use of the fluopi module to analyse time-lapse image data. Sample image data is included in the relevant folders. You can start from these examples, switching the file paths to your data. ## Authors **Universidad Catolica de Chile** * Isaac Nuez - [Prosimio](https://github.com/Prosimio) * Tamara Matute - [tfmatute](https://github.com/tfmatute) * Juan Keymner - [Keymer Lab](http://keymerlab.nl/www/?page_id=26) * Tim Rudge - [Rudge lab](http://rudge-lab.org) * Fernan Federici - [Federici lab](https://federicilab.org) [**Backyard Brains Chile**](http://www.backyardbrains.cl/) * Roberto Pellizzari - [RoHPellizzari](https://github.com/RoHPellizzari) * Tim Marzullo - [Backyard Brains](http://www.backyardbrains.cl/) ## License This project is licensed under the MIT License - see the [LICENSE.txt](LICENSE.txt) file for details. Hardware is lincesed under the CERN license. ## FAQs and updates Please follow updates, ask questions and check FAQs in this [doc](https://docs.google.com/document/d/1-tSU8xBUZicgM2oZv8TOGw7QUYI85IWkbmjetRthfG8/edit?usp=sharing) ## Acknowledgments * _Toby Wenzel_ for guidance on Docubricks documentation * _Tom Baden_ and _Andre Chagas_ for feedback and advice on camera * _Bernardo Pollak_ for helping out with sequences * _Douglas Densmore_ for the CIDAR MoClo Parts Kit * _OpenPlant Fund_ and _Fondecyt_ for providing financial support [wiki]: https://github.com/SynBioUC/FluoPi/wiki [website]: https://osf.io/dy6p2/
![]()
Owner
- Name: Rudge Lab
- Login: RudgeLab
- Kind: organization
- Website: rudge-lab.org
- Twitter: rudgelab
- Repositories: 10
- Profile: https://github.com/RudgeLab
GitHub Events
Total
- Fork event: 1
Last Year
- Fork event: 1
Committers
Last synced: almost 3 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| RoHPellizzari | r****p@g****m | 130 |
| Prosimio | i****z@u****l | 129 |
| Tim Rudge | t****e@g****m | 63 |
| FernanFederici | f****i@b****l | 25 |
| Prosimio | i****l | 8 |
| Tim Rudge | t****e | 5 |
| gyanezfeliu | g****u@g****m | 2 |
| chepo92 | a****a@u****l | 1 |
| amchagas | a****s@g****m | 1 |
Committer Domains (Top 20 + Academic)
uc.cl: 2
bio.puc.cl: 1
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 2
- Total pull requests: 8
- Average time to close issues: N/A
- Average time to close pull requests: 4 days
- Total issue authors: 2
- Total pull request authors: 5
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 5
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- amchagas (1)
- jcmolloy (1)
Pull Request Authors
- RoHPellizzari (3)
- chepo92 (2)
- amchagas (1)
- iacobo (1)
- jcahill (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
setup.py
pypi
- matplotlib *
- numpy *
- scikit-image *
- scipy *
][website]
Hardware design files, code and teaching materials for a low cost and open source fluorescent image registration station.
## Overview
FluoPi is composed of a blue-light transilluminator, an amber acrylic filter and a raspberry camera contained in a black acrylic mainframe. All the hardware is controlled with a Raspberry pi small computer.
With this equipment you are able to:
* Take images of fluorescent samples ranges from um to cm.
* Perform timelapse assays of up to 3 fluorescent proteins simultaneously
* See electrophoresis gel stained with blue excitable chemicals (such as GelRed or SYBR Safe).
## Getting Started
You can see the full project at [OSF](https://osf.io/dy6p2/)
and a pre-print manuscript at [Biorxiv](https://www.biorxiv.org/content/early/2017/09/27/194324) and peer-reviewed article in [PLoS](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187163)
### Prerequisites
To assemble this device you need access to a laser cutter and a 3D printer. You also need a mouse, keyboard and a screen
with HDMI (or hdmi to VGA adaptor) to connect with the Raspberry pi (you can also manage the equipment through SSH or using programs such as [teamviewer](https://pages.teamviewer.com/published/raspberrypi/))
### Installing
All the installation instructions are available on the [wiki page][wiki]
Full documentation and assembly instructions can be found at [Docubricks](http://docubricks.com/viewer.jsp?id=701517893260717056)
### Running the equipment
The equipment has a manual switch and the camera can be controlled with [_camera module commands_](https://www.raspberrypi.org/documentation/usage/camera/raspicam/README.md).
The project includes some python codes (based on [camera python module](https://www.raspberrypi.org/documentation/usage/camera/python/)) to control the hardware:
* _timelapse.py_ --> to perform timelapse experiments
* _turnON.py_ --> to turn ON the transilluminator
* _turnOFF.py_ --> to turn OFF the transilluminator
### Running the notebooks
Jupyter notebooks are included (Examples/ and Tutorials/) to demonstrate the analysis principles and the use of the fluopi module to analyse time-lapse image data. Sample image data is included in the relevant folders. You can start from these examples, switching the file paths to your data.
## Authors
**Universidad Catolica de Chile**
* Isaac Nuez - [Prosimio](https://github.com/Prosimio)
* Tamara Matute - [tfmatute](https://github.com/tfmatute)
* Juan Keymner - [Keymer Lab](http://keymerlab.nl/www/?page_id=26)
* Tim Rudge - [Rudge lab](http://rudge-lab.org)
* Fernan Federici - [Federici lab](https://federicilab.org)
[**Backyard Brains Chile**](http://www.backyardbrains.cl/)
* Roberto Pellizzari - [RoHPellizzari](https://github.com/RoHPellizzari)
* Tim Marzullo - [Backyard Brains](http://www.backyardbrains.cl/)
## License
This project is licensed under the MIT License - see the [LICENSE.txt](LICENSE.txt) file for details. Hardware is lincesed under the CERN license.
## FAQs and updates
Please follow updates, ask questions and check FAQs in this [doc](https://docs.google.com/document/d/1-tSU8xBUZicgM2oZv8TOGw7QUYI85IWkbmjetRthfG8/edit?usp=sharing)
## Acknowledgments
* _Toby Wenzel_ for guidance on Docubricks documentation
* _Tom Baden_ and _Andre Chagas_ for feedback and advice on camera
* _Bernardo Pollak_ for helping out with sequences
* _Douglas Densmore_ for the CIDAR MoClo Parts Kit
* _OpenPlant Fund_ and _Fondecyt_ for providing financial support
[wiki]: https://github.com/SynBioUC/FluoPi/wiki
[website]: https://osf.io/dy6p2/