Setup – High dimensional statistics with R

It’s usually recommended that course instructors provide a virtual environment with software and data available. However this page includes instructions to set up for the lessons. This should take about an hour to run, depending on the speed of your computer, your internet connection, and any packages you have installed already. You’ll need to install R 4.0 or later.

The following code will download the data and install the libraries used in the current version of this lesson:

install.packages("BiocManager")
download.file(
    "https://raw.githubusercontent.com/carpentries-incubator/high-dimensional-stats-r/gh-pages/dependencies.csv",
    destfile = 'dependencies.csv'
)
table <- read.table('dependencies.csv')
BiocManager::install(table[[1]])

dir.create("data", showWarnings = FALSE)
data_files <- c(
    "cancer_expression.rds",
    "coefHorvath.rds",
    "methylation.rds",
    "scrnaseq.rds",
    "prostate.rds",
    "cres.rds"
)
for (file in data_files) {
    download.file(
        url = file.path(
            "https://raw.githubusercontent.com/carpentries-incubator/high-dimensional-stats-r/gh-pages/data",
            file
        ),
        destfile = file.path("data", file)
    )
}

On Linux systems, part of the above may fail due to the bluster package and you may receive error messages after running BiocManager::install(table[[1]]), indicating that the package igraph was not installed successfully.

Detailed installation instructions for igraph can be found at https://r.igraph.org/, but the following workaround code may resolve the issue:

install.packages('igraph', repos=c(igraph = 'https://igraph.r-universe.dev', 
                                   CRAN = 'https://cloud.r-project.org'))
                                   
BiocManager::install('bluster')

Note especially the C libraries that are mentioned on the igraph help page for compiling from source — these are usually available via a package manager (homebrew, apt, pacman, etc), and are required if your R installation is unable to use pre-compiled binaries from CRAN.

High dimensional statistics with R: Setup