Chapter 2 Install

Here, we have provided several ways to install UCSCXenaShiny R package. You can see the detailed instruction and troubleshooting information from the README file of our Github project.

2.1 CRAN

# Online
install.packages("UCSCXenaShiny")
## or specific repos
install.packages("UCSCXenaShiny", repos = c("https://openbiox.r-universe.dev", "https://cran.r-project.org"))

# Local
install.packages("UCSCXenaShiny_2.0.0.tar.gz", repos = NULL, type="source")
  • Once the package has been installed successfully, your can load it and check its version:
library(UCSCXenaShiny)
## =========================================================================================
## UCSCXenaShiny version 2.2.0
## Project URL: https://github.com/openbiox/UCSCXenaShiny
## Usages: https://openbiox.github.io/UCSCXenaShiny/
## 
## If you use it in published research, please cite:
##   Shixiang Wang, Yi Xiong, Longfei Zhao, Kai Gu, Yin Li, Fei Zhao, Jianfeng Li,
##   Mingjie Wang, Haitao Wang, Ziyu Tao, Tao Wu, Yichao Zheng, Xuejun Li, Xue-Song Liu,
##   UCSCXenaShiny: An R/CRAN Package for Interactive Analysis of UCSC Xena Data,
##   Bioinformatics, 2021;, btab561, https://doi.org/10.1093/bioinformatics/btab561.
## =========================================================================================
##                               --Enjoy it--
packageVersion("UCSCXenaShiny")
## [1] '2.2.0'

2.2 Github

# Online
devtools::install_github("openbiox/UCSCXenaShiny")

# Local
devtools::install_local(path = "UCSCXenaShiny-master.zip")

2.3 Conda

conda install -c conda-forge r-ucscxenashiny
  • list all of the versions of r-ucscxenashiny available on your platform:
conda search r-ucscxenashiny --channel conda-forge

2.4 Docker

# install image
docker pull shixiangwang/ucscxenashiny

# run image
docker run -d --name xenashiny -p 3838:3838 shixiangwang/ucscxenashiny