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mdminershiny's Introduction

THE OHIO STATE UNIVERSITY

Repositioning Drugs for Individual Cancer Patients based on Personal Genomics using Precision Medicine

mdMiner is an innovative web application that uses machine learning approaches to predict the best drugs and drug combinations for individual cancer patients using their genomic data. mdMiner is an application developed by the Department of Biomedical Informatics at The Ohio State University College of Medicine under the supervision of Dr. Fuhai Li.

Installing

  1. Install R on your machine following the instructions on any of these links.
    Windows - https://cran.r-project.org/bin/windows/base/
    Linux - https://cran.r-project.org/doc/manuals/r-release/R-admin.html
    Mac OS X - https://cran.r-project.org/bin/macosx/

  2. Download and install the latest version of RStudio
    https://www.rstudio.com/products/rstudio/download2/#download

  3. Install Shiny and ShinyDashboard packages by typing the following commands on the R console.
    > install.packages("shiny");
    > install.packages("shinydashboard");

  4. Install other dependencies by typing the following commands on the R console.
    > install.packages("RCurl");
    > install.packages("networkD3");
    > install.packages("httr");
    > install.packages("DT");
    > install.packages("igraph");

  5. Use Bioconductor as following to install Graphite and Genome annotation packages. Type the following commands in R console.
    > source("https://bioconductor.org/biocLite.R");
    > biocLite();
    > biocLite("graphite”);
    > biocLite("org.Hs.eg.db”);

Instructions

Click Run App in RStudio. This will open the webapp in a browser.
Click on the Choose File button and upload fold change data of a patient in a .txt file format.
Drug suggestions will be generated in descending order.
Click the desired drug in the table to display drug network, gene network and the merge network.
Click the title of each block to download corresponding data.

For any questions, please contact: [email protected].

#####- Dr. Fuhai Li - Department of Biomedical Informatics, The Ohio State University.

To deploy the app on AWS

  1. Launch a Ubuntu instance on AWS. Follow instruction: http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EC2_GetStarted.html#ec2-launch-instance_linux. When configuring security group, open protocol HTTP and SSH, which opens port 80 and 22 respectively. Set the source of port 22 to your own IP only. Also use Custom TCP RULE to open port 3838 for shiny application.
  2. Conncet instance using public key provided by Amazon. For detail instruction: http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html
  3. Install shiny server on your instance. Follow instruction: https://www.rstudio.com/products/shiny/download-server/
  4. Make a directory for your app in /srv/shiny-server. Change the mode of the new folder to 771.
  5. Use scp to transfer your shiny project to the new folder you create under /srv/shiny-server.

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