Installation¶
There are three different ways to install UROPA. We recommend to install UROPA using the conda package manager.
Conda package manager¶
Make sure to have conda installed, e.g. via
- Miniconda
- download the Miniconda installer for Python 3
- run
bash Miniconda3-latest-Linux-x86_64.sh
to install Miniconda - Answer the question “Do you wish the installer to prepend the Miniconda install location to PATH in your /home/…/.bashrc ?” with yes
- OR do
export PATH=dir/to/miniconda3:$PATH
after installation process
The UROPA installation is now as easy as
conda create --name uropa
conda activate uropa
conda install python uropa
.
Biocontainers / Docker¶
If you have a running Docker environment, you can pull a biocontainer with UROPA and all dependencies via
docker pull quay.io/biocontainers/uropa:latest_tag
using the latest tag from the taglist, e.g.1.2.1--py27r3.3.2_0
docker pull loosolab/uropa
Installation from source¶
You can also install UROPA from the source PyPI package. Note that this comes without the R dependencies for auxillary scripts:
pip install uropa
To fulfill all other dependencies, R/Rscript, v3.3.0 or higher (follow the instructions on url) is needed. Futhermore, follow the subsequent instructions within R environment to install mandatory packages:
install.packages(c("ggplot2","devtools","gplots","gridExtra","jsonlite", "VennDiagram","snow","getopt","tidyr","UpSetR"))
source("https://bioconductor.org/biocLite.R")
biocLite(c("RBGL","graph"))
- further package infos can be found at CRAN and Bioconductor
- In order to visualize the Chow-Ruskey plot with uropa_summary.R, install the modified Vennerable package from our fork:
library(devtools)
install_github("jenzopr/Vennerable")