MAGI
MAGI is a platform for interactive visualization and collaborative annotation of combinations of genetic aberrations. MAGI allows users to upload their own private datasets and view and annotate them in combination with public datasets.
This repository contains the source code for MAGI. MAGI is written in Node.js with a MongoDB database. MAGI uses D3, jQuery, and GD3 on the front-end. Below, we describe how to get a version of MAGI running on your personal machine.
Dependencies
- Node.js and NPM (included with Node.js).
- MongoDB. Make sure you can run
mongodfrom your terminal. Some basic debugging tips are:- Make sure that you make a directory to store the database. The default is
/data/db, so you'll need to make that directory before runningmongod. - Make sure that the
mongod,mongo, etc. are in yourPATH.
- Make sure that you make a directory to store the database. The default is
- Python. Tested with version 2.7.x.
- PyMongo to load data into MAGI.
- Numpy, SciPy, and Scikit-Learn to compute the statistical association of mutations with different sample annotations/categories, or the (dis)similarity of different sample annotations/categories.
MAGI has been tested on both Linux and Mac systems using Chrome, Firefox, and Safari.
MAGI Annotations
Please follow the instructions on setting up MAGI annotations to include protein to include protein-protein interactions and mutation annotations in MAGI.
Setup
Setup consists of five basic steps:
- Install Node, Python, and MongoDB (as described above).
- Create an
ENVIRONMENTfile with your settings, with oneexport VARIABLE_NAME="..."per line. Make sure to load the environment variables into whatever shell you are running. We provide more information below. - Run (possibly a subset of the ) commands in
setup.shto install dependencies, download data, and initialize the database. We provide more information below. - Start the server with
node server, which serves tohttp://localhost:8000by default.
Environment
Set the following environment variables to customize MAGI.
General
| Name | Default | Description |
|---|---|---|
NODE_ENV |
development | Environment: production for publicly available on the web, or development for local/testing. |
PORT |
8080 | Port from which you are serving MAGI |
SITE_URL |
localhost | Domain name from which you are serving MAGI |
MONGO_DB_NAME |
magi | Name of database in MongoDB you want to use for MAGI |
Third-party services
To use authentication with MAGI, you will need to obtain Google OAuth2 credentials and set the appropriate environment variables. Similarly, to use the MAGI feedback tool you will need to obtain a WebEngage ID.
| Name | Default | Description |
|---|---|---|
GOOGLE_CLIENT_ID |
None | Google OAuth2 client ID |
GOOGLE_CLIENT_SECRET |
None | Google OAuth2 client secret |
WEBENGAGE_ID |
None | WebEngage ID for Javascript SDK integration |
If you want to be a webmaster for your version of MAGI on Google and Bing, you will need MAGI to serve XML files. Google and Bing will provide the XML files and specific paths/names, which you can set with the following variables.
| Name | Default | Description |
|---|---|---|
GOOGLE_SEO_ROUTE |
None | Local path to Google SEO XML file |
GOOGLE_SEO_ROUTE_NAME |
None | Name of Google XML file route |
BING_SEO_ROUTE |
None | Local path to Google SEO XML file |
MAGI annotations
MAGI can retrieve protein-protein interactions and mutation annotations from a MAGI annotations Postgres database. To do so, set the following environment variables.
| Name | Default | Description |
|---|---|---|
POSTGRES_DJANGO_DBNAME |
magipy | Name of Postgres database |
POSTGRES_DJANGO_HOST |
127.0.0.1 | Name of Postgres host |
POSTGRES_DJANGO_PORT |
5432 | Name of Postgres port |
POSTGRES_DJANGO_USER |
postgres | Name of Postgres user |
POSTGRES_DJANGO_PASSWORD |
None | Password for Postgres user |
DJANGO_ANNOTATIONS_URL |
http://annotations.cs.brown.edu | URL for MAGI annotations server |
Data
We provide a tarball of data used in MAGI (currently ~100Mb) on the Raphael group website. This includes general datasets -- HG19 gene locations, cancer acronyms and descriptions, known gene sets from KEGG and PINdb -- and also mutation datasets.
Support
MAGI was created and is maintained by the Raphael research group in the Center for Computational Molecular Biology and the Department of Computer Science at Brown University. We offer support for MAGI on the MAGI Google Group, or please visit the group website to contact us.
Citation
If you use MAGI in your work please cite
M.D.M. Leiserson, C.C. Gramazio, J. Hu, H-T. Wu, D.H. Laidlaw, B.J. Raphael. MAGI: visualization and collaborative annotation of genomic aberrations. Nature Methods 12, 483-484 (2015). Publink.