EpidemiumDB is a large public database for Big Data Cancer research. The database is designed to store structured data about more than 200 cancer types, their risk factors, as well as anti-cancers drugs and their side-effects and adverse reactions. In addition, Epidemium provide links to Open datasets collected by collaborators and contributors to the Epidemium Open Science program.
Epidemium is a participatory project launched in France and formed by a multidisciplinary team of highly qualified scientists and experts in Informatics, Data Sciences, Medicine, and pharmacology grouped together with the desire to advance cancer research using Big Data.
Individuals, research institutions, life-science industrials, and organisations who are interested in sharing Open Data related to any type of Cancer can submit to EpidemiumDB their data or a link to their resources. Contributors can either add new datasets, or complete existing ones.
<<<<<<< Updated upstream
- To submit your data to EpidemiumDB, please contact the Epidemium team at data[a]epidemium.cc
- For Epidemium's members, before making a request to add a new table, please check whether similar table is already created.
- If not, please describe your table using the EpidemiumDB Wiki page and send an email to data[a]epidemium.cc or create an issue in the GitHub EpidemiumDB repository.
Stashed changes
Using EpidemiumDB to run any analysis <<<<<<< Updated upstream
- Check if the datasets needed are available
- If no, ask to create the table by sending an email to data[a]epidemium.cc or create an issue in the GitHub EpidemiumDB repository
- Add you own dataset in the EpidemiumDB =======
- Check if the datasets needed are available
- If no, ask to create the table by sending an email to data[a]epidemium.cc or create an issue in the GitHub EpidemiumDB repository
- Add you own dataset in the EpidemiumDB
Stashed changes
EpidemiumDB is a publicly available resource which is freely accessible to Epidemium project members and external people interested in Open Data in Oncology. In addition to a Web interface and visualization evironement, we provide R, Python and Perl scripts to access, query, retrieve, and export EpidemiumDB data.
The R script RMySQLepidemiumDB.R can be used to make direct connection to EpidemiumDB using the RMySQL packages. The later requires DBI library. Using this code, you will be able to make a connection, list tables and fields, retrieve tables, make queries, and export data to text, CVS, Excel, or JSON files. For Excel, the library WriteXLS is used to write an R data frame to excel. For JSON, we used the package df2json (Fig. 1).
#Install RMySQL package
install.packages("RMySQL")
# Load required packages
library("DBI")
library("sqldf")
library("WriteXLS")
library("rjson")
library("jsonlite")
library("df2json")
# Load RMySQL
library(RMySQL)
# Connect to EpidemiumDB
# create a database connection object
# the user, password, host and database name are stored in a separate file
# called connectDB.R that need to be called before bdConnect() function.
setwd("/home/common/database/")
source("connectDB.R")
epidemiumDB = dbConnect(MySQL(), user=user, password=password, dbname=dbname, host=host)
Host name, user, password, and database name are stored in connectDB.R file that need to be called using source() before running the dbConnect() function.
We provide an example script in Python that you can use to connect to EpidemiumDB using MySQLdb
# Install MySQLdb
#!/usr/bin/python
import MySQLdb
# Open database connection
db = MySQLdb.connect(host="host_name", # host name (IP address for Epidemium.cc)
user="username", # your username
passwd="password", # your password
db="epidemiumdb") # name of the database
# Prepare a cursor object using cursor()
cursor = db.cursor()
# Send and SQL query using execute()
cursor.execute("SELECT VERSION()")
# Fetch a single row using fetchone()
data = cursor.fetchone()
print "Database version : %s " % data
cursor.execute("SELECT * FROM metadata")
rows = cursor.fetchall()
DBI is the standard database interface module for Perl. The script PerlEpidemiumDB.pl provides functionalities for Perl/EpidemiumDB interface.
#!/usr/bin/perl
use strict;
use warnings;
use DBI;
my $dbfile = "epidemiumdb";
my $dsn = "dbi:SQLite:dbname=$dbfile";
my $user = "";
my $password = "";
my $dbh = DBI->connect($dsn, $user, $password, {
PrintError => 0,
RaiseError => 1,
AutoCommit => 1,
FetchHashKeyName => 'NAME_lc',
});
....
$dbh->disconnect;
EpidemiumDB is based on a relational data model linked to CKAN data management platform.
coming soon
The EpidemiumDB database contains the following tables:
| Table Name | Description | Curation Type |
|---|---|---|
| cancerType | All cancer types | Manual curation and validation by an expert |
| cancerRiskFactor | All known risk factor for cancer | Manual curation and validation by an expert |
| riskFactorGroup | groups of cancer risk factor | Manual curation and validation by an expert |
| riskFactor2publication | All publications about cancer risk factors | data retrieval, text mining, and manual curation |
| antiCancerDrugs | All anti cancers drugs | data retrieval, text mining, and manual curation |
coming soon
- The Wiki page EpidemiumDB (in french) is used to discuss the design and developement of EpidemiumDB.
- A presentation given by Seraya Maouche on April, 7th, 2016 at the Epidemium Meetup is available online.
- A Presentation prepared by Seraya Maouche and presented by Olivier de Fresnoye at the March Meeting of Epidemium is available online.
A manuscript describing EpidemiumDB is under preparation, if you have contributed to EpidemiumDB, please join the collaborative editor project on [Authoria platform] (https://www.authorea.com) in order to contribute to the manuscript.
- For administration issues, do not hesitate to contact the Epidemium team at data[a]epidemium.cc
- For scientific questions, database content, conception and development of EpidemiumdDB, please contact Seraya Maouche (seraya.maouche[a]iscb.org)
- For cancer epidemiological data, please contact Edouard Debonneuil (edebonneuil[a]yahoo.fr).