ST Spot Detector

A web tool for automatic spot detection and positional adjustments for ST datasets.

The arrays used to generate ST datasets may contain positional variations due to printing artifacts. This web tool aims to detect correct spot positions using the images generated from the ST protocol. In order to obtain relevant experimental data, it is also possible to automatically select the spots which are located under the tissue, using a corresponding HE image. The spot positions and selections are further adjustable to one's own needs. A file is generated which contains the corrected spot coordinates of the ST data as adjusted array coordinates and pixel coordinates as well as file containing a 3x3 affine matrix to transform array coordinates to pixel coordinates which can be useful for downstream analysis.

Dependencies

The following packages are required:

Python 3.6+
Node.js 10.0+
npm 6.0+

Additionally, the ST tissue recognition library needs to be installed.

A modern browser is required for the front-end interface. The web app has been tested on Chrome 66 and Firefox 60.

Usage

If you want to deploy the ST Spot detector locally on your computer you can use this singularity container. Otherwise follow the deployment instructions below.

Download

1. Clone the repository

   git clone https://github.com/SpatialTranscriptomicsResearch/st_spot_detector.git
   

2. Move into the directory

   cd st_spot_detector
   

Server setup

1. Install the dependencies

2. Create and activate a Python virtual environment

   pip install virtualenv
   virtualenv venv
   source venv/bin/activate
   

3. Install the dependencies in requirements.txt.

   cd server
   pip install -r requirements.txt
   

4. Install the tissue recognition library (still within the Python virtual environment). Follow the instructions here.

5. Build the client side files:

   cd ../client
   npm install
   make dist
   

6. Run the server with the following command:

   cd ../server
   python -m app
   

   The server is WSGI-compatible and can, alternatively, be run with a WSGI server of your choice.

7. Optional. It may be desirable to configure port-forwarding to be able to access the web tool through port 80, e.g. using iptables:

   sudo iptables -t nat -A PREROUTING -p tcp --dport 80 -i eth0 -j DNAT --to 0.0.0.0:8080
   
   

For any queries or concerns, feel free to contact the authors at the addresses given below.

Citation

If you want to cite the ST Spot detector:

ST Spot Detector: a web-based application for automatic spot and tissue detection for Spatial Transcriptomics image data sets DOI: 10.1093/bioinformatics/bty030

Manual

For a guide on using the ST spots detection tool, please refer to this guide.

License

MIT (see LICENSE).

Authors

See AUTHORS.

Contact

Kim Wong [email protected]

Ludvig Bergenstråhle [email protected]

Jose Fernandez [email protected]