Installing and Using R Packages


In our previous articles, we published i) guides for installing and launching R/RStudio, ii) the basics of R programming, and ii) guides for finding help in R.


Here, we’ll describe:

  • what is an R package
  • and how to install and use R packages


What is R packages?

An R package is an extension of R containing data sets and specific functions to solve specific questions.

R comes with standard (or base) packages, which contain the basic functions and data sets as well as standard statistical and graphical functions that allow R to work.

There are also thousands other R packages available for download and installation from CRAN, Bioconductor and GitHub repositories.

After installation, you must first load the package for using the functions in the package.

Installing R packages

Packages can be installed either from CRAN (for general packages), from Bioconductor (for biology-related packages) or from Github (developing versions of packages).

Install a package from CRAN

The function install.packages() is used to install a package from CRAN. The syntax is as follow:

install.packages("package_name")

For example, to install the package named readr, type this:

install.packages("readr")

Note that, every time you install an R package, R may ask you to specify a CRAN mirror (or server). Choose one that’s close to your location, and R will connect to that server to download and install the package files.

It’s also possible to install multiple packages at the same time, as follow:

install.packages(c("readr", "ggplot2"))

Install a package from Bioconductor

Bioconductor contains packages for analyzing biological related data. In the following R code, we want to install the R/Bioconductor package limma, which is dedicated to analyse genomic data.

To install a package from Bioconductor, use this:

source("https://bioconductor.org/biocLite.R")
biocLite("limma")

Install a package from Github

GitHub is a repository useful for all software development and data analysis, including R packages. It makes sharing your package easy. You can read more about GitHub here: Git and GitHub, by Hadley Wickham.

To install a package from GitHub, the R package devtools (by Hadley Wickham) can be used. You should first install devtools if you don’t have it installed on your computer.

For example, the following R code installs the latest version of survminer R package developed by A. Kassambara (https://github.com/kassambara/survminer).

install.packages("devtools")
devtools::install_github("kassambara/survminer")

View the list of installed packages

To view the list of the already installed packages on your computer, type :

installed.packages()

Note that, in RStudio, the list of installed packages are available in the lower right window under Packages tab (see the image below).

installed packages, RStudio

Folder containing installed packages

R packages are installed in a directory called library. The R function .libPaths() can be used to get the path to the library.

.libPaths()
[1] "/Library/Frameworks/R.framework/Versions/3.2/Resources/library"

Load and use an R package

To use a specific function available in an R package, you have to load the R package using the function library().

In the following R code, we want to import a file (“http://www.sthda.com/upload/decathlon.txt”) into R using the R package readr, which has been installed in the previous section.

The function read_tsv() [in readr] can be used to import a tab separated .txt file:

# Import my data
library("readr")
my_data <- read_tsv("http://www.sthda.com/upload/decathlon.txt")
# View the first 6 rows and tge first 6 columns
# syntax: my_data[row, column]
my_data[1:6, 1:6]
     name  100m Long.jump Shot.put High.jump  400m
1  SEBRLE 11.04      7.58    14.83      2.07 49.81
2    CLAY 10.76      7.40    14.26      1.86 49.37
3  KARPOV 11.02      7.30    14.77      2.04 48.37
4 BERNARD 11.02      7.23    14.25      1.92 48.93
5  YURKOV 11.34      7.09    15.19      2.10 50.42
6 WARNERS 11.11      7.60    14.31      1.98 48.68

View loaded R packages

To view the list of loaded (or attached) packages during an R session, use the function search():

search()
 [1] ".GlobalEnv"        "package:readr"     "package:stats"     "package:graphics" 
 [5] "package:grDevices" "package:utils"     "package:datasets"  "package:methods"  
 [9] "Autoloads"         "package:base"     

If you’re done with the package readr and you want to unload it, use the function detach():

detach("readr", unload = TRUE)

Remove installed packages

To remove an installed R package, use the function remove.packages() as follow:

remove.packages("package_name")

Update installed packages

If you want to update all installed R packages, type this:

update.packages()

To update specific installed packages, say readr and ggplot2, use this:

update.packages(oldPkgs = c("readr", "ggplot2"))

Summary


  • install.packages(“package_name”): Install a package

  • library(“package_name”): Load and use a package

  • detach(“package_name”, unload = TRUE): Unload a package

  • remove.packages(“package_name”): Remove an installed package from your computer

  • update.packages(oldPkgs = “package_name”): Update a package


Infos

This analysis has been performed using R software (ver. 3.2.3).









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