An R package containing functions for assessing the replication and preservation of a network module's topology across datasets through permutation testing. This is suitable for networks that can be meaningfully inferred from multiple datasets. These include gene coexpression networks, protein-protein interaction networks, and microbial interaction networks. Modules within these networks consist of groups of nodes that are particularly interesting: for example a group of tightly connected genes associated with a disease, groups of genes annotated with the same term in the Gene Ontology database, or groups of interacting microbial species, i.e. communities. Application of this method can answer questions such as; (1) do the relationships between genes in a module replicate in an independent cohort? (2) are these gene coexpression modules preserved across tissues or tissue specific? (3) are these modules conserved across species? (4) are microbial communities preseved across multiple spatial locations?
The main function for this package is modulePreservation
, which
performs the permutation test procedure. Other useful functions include
networkProperties
for calculating the topological properties of a
module, and plotModule
for visualising a network module.
For more information see the associated publication in Cell Systems, A Scalable Permutation Approach Reveals Replication and Preservation Patterns of Network Modules in Large Datasets.
The latest stable version of NetRep can be installed either directly from CRAN or from this GitHub repository:
# From CRAN
install.packages("NetRep")
# Alternatively From GitHub
library(devtools)
install_github("InouyeLab/NetRep")
Developmental / pre-release versions of NetRep can be installed from this repository:
library(devtools)
install_github("InouyeLab/NetRep", ref="devel")
Older versions of NetRep can be installed by specifying the version number in the ref
argument:
install_github("InouyeLab/NetRep", ref="v0.61.0")
A vignette (tutorial) is available online at vignettes/NetRep.md,
or can be loaded directly from R by running vignette("NetRep")
if you have installed
the package from CRAN.
If you are installing NetRep from GitHub and wish to make the vignette available on your
local machine, you will need to install rmarkdown
and specify build_vignettes=TRUE
when running install_github
.
NetRep and its dependencies require several third party libraries to be installed. If not found, installation of the package will fail.
- A compiler with
C++11
support for the<thread>
libary. - A
fortran
compiler. BLAS
andLAPACK
libraries.
The necessary C++11
compilers are provided with the Xcode
application and subsequent installation of Command line tools
. The most
recent version of OSX should prompt you to install these tools when
installing the devtools
package from RStudio. Those with older versions of
OSX should be able to install these tools by typing the following command into
their Terminal application: xcode-select --install
.
The necessary fortran
compiler depends on both the OSX version and R version
installed by the user. The "R for Mac OS X" page on CRAN
provides instructions for determining the correct fortran version as well as
relevant download links.
NetRep can be installed on Windows in R version 3.3.0 or later. The
necessary fortran
and C++11
compilers are provided with the Rtools
program. We recommend installation of NetRep
through RStudio
, which should
prompt the user and install these tools when running
devtools::install_github("InouyeLab/NetRep")
. You may need to run this
command again after Rtools finishes installing.
If installation fails when compiling NetRep at permutations.cpp
with an
error about namespace thread
, you will need to install a newer version of
your compiler that supports this C++11
feature. We have found that this works
on versions of gcc
as old as gcc-4.6.3
.
If installation fails prior to this it is likely that you will need to install
the necessary compilers and libraries, then reinstall R. For C++
and
fortran
compilers we recommend installing g++
and gfortran
from the
appropriate package manager for your operating system (e.g. apt-get
for
Ubuntu). BLAS
and LAPACK
libraries can be installed by installing
libblas-dev
and liblapack-dev
. Note that these libraries must be
installed prior to installation of R.