This is the source code of "DREAM: an R package for druggability evaluation of human complex diseases". DREAM focuses on assessing the druggability of specific pathological conditions by leveraging robust drug repurposing predictions. It provides a powerful tool for identifying potential sets of drugs putatively suitable for combination therapy.
To create the necessary environment use the following command
⚠️ note: the environment has only been tested on Linux! For other systems please refer to the Docker section
conda env create --file environment.yml -n dream
After creating the environment run the following commands to complete the installation of the required dependencies
conda run -n dream R -e "install.packages('TopKLists', dependencies=FALSE, repos='http://cran.us.r-project.org')"
conda run -n dream R -e "devtools::install_github('filosi/nettools', dependencies=FALSE, upgrade_dependencies=FALSE)"
conda run -n dream R -e "install.packages('IRkernel', dependencies=FALSE, repos='http://cran.us.r-project.org'); IRkernel::installspec()"
conda run -n dream R -e "install.packages('https://github.com/fhaive/dream/releases/download/public/DREAM_0.1.0.tar.gz', repos=NULL)"
conda run -n dream pip install https://github.com/fhaive/dream/releases/download/public/dream-0.1.dev0-py3-none-any.whl
The environment provides a Jupyter server in which it is possible to run R code and perform analyses with DREAM. To start the Jupyter server run the following command:
conda run -n dream jupyter lab --NotebookApp.token='' --NotebookApp.password=''
And browse to the address http://localhost:8888/lab
It is possible to either start from a new notebook, or open the provided notebooks that shows how to use the functionalities provided by the package.
Specifically, the notebook dream_vignette.ipynb shows how the analysis reported as the case study described in Supplementary File 2 of the publication was performed.
We also provide a ready made docker environment to try the package that can be launched using the command
docker run -it --rm -p8888:8888 -e UID=$(id -u) -e GID=$(id -g) -v$(pwd):/workspace fhaive/dream:latest
This will start the same jupyter environment within the docker that can be accessed in the same manner browsing the page http://localhost:8888/lab
In addition, the current directory in which the command is executed will be mapped inside the docker container, facilitating data exchange.
To build the docker image from scratch, use the following commands:
# clone the repository
git clone [email protected]:fhaive/dream.git
cd dream/
docker build -t dream .
# after building, run the container
docker run -it --rm -p8888:8888 -e UID=$(id -u) -e GID=$(id -g) -v$(pwd):/workspace dream