randomGLM package FAQ

Lin Song, Peter Langfelder and Steve Horvath

Human Genetics and Biostatistics, University of California, Los Angeles

shorvath (at) mednet (dot) ucla (dot) edu

This page provides a list of Frequently Asked Questions and our frequently given answers. Please read
these before emailing us about a problem.

General questions

  1. Can randomGLM use multiple processors (parallel threads)?Yes, see the argument nThreads.

    Some calculations can use parallel execution (multi-threading) to gain speed. Currently, multi-threading is
    only available on POSIX-compliant systems such as varius Linux and Unix flavors and Mac OS. It is not
    available on Windows, sorry.

    Even on systems where threading is available it is disabled by default. This is a conservative setting
    that may slow down the calculations but will also prevent WGCNA from grabbing all available processor
    There are two ways to enable multi-threading:

    • Within R, call the function

      to allow threading from within WGCNA. Multi-threading can be turned off
      again using the function disableWGCNAThreads(). See the help file for
      allowWGCNAThreads() for more details.

    • Set the environment variable

      for example, if
      you have 2 cores (or want to use 2 cores),



      If you don’t know what an
      environment variable is, please use the above allowWGCNAThreads() within R.

    Please note that this setting does not affect the multi-threading status of the underlying BLAS library.

  2. Is there a GUI interface to WGCNA?In short, no. There used to be one but it is hopelessly broken and out of date.

Installation problems

  1. Package impute is not availableAs of R version 2.14.0, the package impute has been withdrawn from CRAN and is now available
    exclusively from Bioconductor. To install it, type the following lines in an R session:
  2. Most installation problems can be solved by using CRAN!Before you spend time trying to solve an installation problem with the downloaded package, please consider
    installing the package from CRAN. We understand that upgrading R can be abit of a hassle, but in the end
    it’s worth it.
  3. R complains about wrong package type.A common cause of this error is that when the user saves the file, the operating system will uncompress
    or unzip it.
    Typically, this means the .zip or .tar.gz bundle will be decompressed and extracted, which renders the
    file unusable for R. For example, Mac OS X seems to automatically decompress the gzipped file.
    The solution is to save the file to disk as is, without letting any program such as
    WinZip touch it. R will decompress and unpack the package itself. On a Mac, you may have to open a
    terminal, change to the directory where you saved the file, and type

    gzip WGCNA_*.tar


  4. The package won’t install on my Mac.The best solution is to update your R to the newest version, then simply run R and use the command
    install.packages("randomGLM"). If you for some reason cannot or do not want to update your R,
    please look at the installation instructions and make
    sure you have the required XCode tools installed.
  5. I have Xcode tools installed and the package still won’t install.Some users have reported that a package named gfortran.pkg is also necessary.
    This may be a new feature of R as of version 2.9.0.