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Installation

install.Rmd

In this package, we frequently solve an ordinary differential equation model in the context of biological experiments. This can be done using deSolve, but we prefer to use gsl_odeiv2, for whcih we have written a binding into R (called rgsl). The user facing interface is designed around the idea of experiments and is more convenient (and faster). To use this simulation backend, your system requires the gnu scientific library, which R cannot install by itself, usually the admin of your machine can do this. If that is you and you don’t have GSL yet, then follow the guide in the next section.

We know that it is in principle possible to use this package on windows, but have no experience with this, and cannot provide instructions or help with problems.

GNU Scientific Library (optional)

For the simulation backend using the GNU Scientific Library (gsl, odeiv2), the library needs to be installed in your OS, it is not an R package (it’s a library dependency).

To compile sources with gsl requires c compiler options related to linking and the librarie’s location. They can look like this: -lgsl -lgslcblas -lm, but also more complex (this depends on your system). We use pkg-config to determine the right options (or pkgconf, which does the same thing (but faster)). If pkg-config is missing from the system, installation will fail (it is available for MAC, GNU Linux, Unix, BSD, and Windows).

Operating System install gsl install pkg-config
Debian and Ubuntu sudo apt install libgsl-dev sudo apt install pkg-config
Alpine Linux sudo apk add gsl sudo apk add pkgconf
GNU Guix guix install gsl guix install pkg-config
Arch Linux sudo pacman -S gsl sudo pacman -S pkgconf
Gentoo sudo emerge sci-libs/gsl sudo emerge virtual/pkgconfig
MACOS brew install gsl brew install pkg-config or pkgconf

Once gsl and pkg-config are available on the system, the icpm-kth/rgsl package should compile nicely.

If you are in a normal user shell (not a root shell, su -), and not using guix or NixOS, then the commands require sudo or doas in front of them to have the required system administration rights. GNU Guix and NIXOS have package managers that don’t require administration rights.

R itself

Availability of specific versions depend on the version of your OS, how up-to-date your package database. Here is a quick list of the approximate command:

Operating System install R
Alpine linux sudo apk add R
Debian/Ubuntu sudo apt install r-base
GNU Guix guix install r
Arch sudo pacman -S r
Gentoo emerge --ask dev-lang/R

On MAC, please follow the instructions on the R-studio web-site.

We do not have experience with R on windows, specifically when it comes to GSL and C compilers to compile the C code included in an R package, it may just work, but if not, then maybe these could help:

R packages

Your system’s package manager may have system-wide R packages, e.g.: ubuntu has r-cran-desolve, such that sudo apt install r-cran-desolve would install the deSolve package for all users of your machine. In HPC environments this is preferable as user accounts can have harsh quotas on file sizes and file numbers.

But, R packages can also be installed from within R (for individual users), but only to a location that is writable to you, typically in your $HOME diectory. Please ensure that .libPaths() returns at least one location that you have write access to.

If not, you can create a new directory, and make it known to R:

mkdir -p ~/R/library && echo "R_LIBS=~/R/library" >> ~/.Renviron

Now, you can install R packages from The Comprehensive R Archive Network cran and github:

install.packages("remotes")

Our packages are not on CRAN, and can be installe dlike this:

remotes::install_github("icpm-kth/uqsa")

Installation of Companion packages

We have developed two companion packages:

  • rgsl
    • solves ODEs with an interface organised around simulation experiments
    • uses solvers from the GNU Scientific Library
    • is used in most of our examples
  • SBtabVFGEN
    • organises the storage and loading of models
    • loads SBtab content from tsv, ods, and excel files
    • creates vfgen, MOD, sbml, and format free ODE files
    • also loads biological data contained in the SBtab files into R variables (lists of simulation experiment setups)

Both are optional, but recommended (our examples use them).

RGSL

This package solves ODE initial value problems, given as lists of simulation experiments, with sudden interventions (like activation, or a sudden signal).

remotes::install_github("icpm-kth/rgsl")       # requires gsl in your OS, see above

This can be replaced with the standard solvers in the deSolve package. In our examples, the solvers in deSolve are always slower.

SBtab Model Handling

This package loads a model written in the SBtab format, which is designed for models in systems biology, but much easier to read than SBML:

remotes::install_github("icpm-kth/SBtabVFGEN") # if you plan to use SBtab

This can be replaced, if you have a different method of model creation or want to write the model source files by hand (which is hard for large models).

Installation of UQSA 

remotes::install_github("icpm-kth/uqsa")       # this package
library(uqsa)                                  # to load it

Read the articles on this website, especially the Example articles to learn more: AKAR4, AKAP79, and CaMKII.

Examples in the Package

The package itself also includes example models, with a run script for each of them. We advise users to copy the run scripts either from the repository or the installed package and adapt them. The location of a run file can be found like this:

uqsa::uqsa_example("AKAP79",pat="^run.*R$")

or by browsing the folders on GitHub (inst/extdata/). Copy one of them and adapt it to your needs.