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")