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jderoberts authored Aug 19, 2019
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Expand Up @@ -24,7 +24,8 @@ Understanding the network context of associations between genes and diseases is
![Application structure](/docs/application_structure.png)

## Application:
The Python application backend maps disease association scores onto networks of interacting proteins, then uses the HotNet2 heat diffusion algorithm to find subnetworks of interacting disease genes. These networks are displayed to the user through an Angular interface as interactive D3.js force-directed graphs, and are annotated with currently available drugs targeting the proteins discovered.
The Python application backend maps disease association scores onto networks of interacting proteins, then uses the HotNet2 heat diffusion algorithm to find subnetworks of interacting disease genes.
These networks are displayed to the user through an Angular interface as interactive D3.js force-directed graphs, and are annotated with currently available drugs targeting the proteins discovered.

![Disease summary](/docs/disease_summary.png)

Expand All @@ -33,25 +34,26 @@ The Python application backend maps disease association scores onto networks of
![Subnetwork drugs](/docs/subnetwork_drugs.png)

## Data Sources:
[Open Targets platform](https://www.opentargets.org/)
[Experimental Factor Ontology](https://www.ebi.ac.uk/efo/)
[STRING](https://string-db.org/)
[OmniPath](http://omnipathdb.org/)
[ChEMBL](https://www.ebi.ac.uk/chembl/)
- [Open Targets platform](https://www.opentargets.org/)
- [Experimental Factor Ontology](https://www.ebi.ac.uk/efo/)
- [STRING](https://string-db.org/)
- [OmniPath](http://omnipathdb.org/)
- [ChEMBL](https://www.ebi.ac.uk/chembl/)

## Setup:
To run the application using the webpack dev server:
1. Install dependencies (Node.js, Angular CLI etc.)
2. Clone the repository
3. Start dev server:
*`cd open-targets-networks/`
*`npm start &`
- `cd open-targets-networks/`
- `npm start &`
4. Start flask backend:
*`cd ../flask-api/`
*`python app.py &`
- `cd ../flask-api/`
- `python app.py &`
5. Open your browser at http://localhost:4200/

The application expects an Elasticsearch instance running at http://localhost:9200/ with an index titled 'efo'. Use the shell scripts included in the [efo-elastic-app/EFO-data](https://github.com/jderoberts/EFO-Elastic-app/tree/master/EFO-data) folder to create the index and populate it with the processed EFO data.
The application expects an Elasticsearch instance running at http://localhost:9200/ with an index titled 'efo'.
Use the shell scripts included in the [efo-elastic-app/EFO-data](https://github.com/jderoberts/EFO-Elastic-app/tree/master/EFO-data) folder to create the index and populate it with the processed EFO data.

## Acknowledgements
My thanks to Jean-Marc Schwartz, Alex Gutteridge and the Open Targets team at GSK.
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