brainGraph (graph theory analysis in R) major release: v2.0.0

Submitted by cgwatson on

Dear DPABI users,

I am pleased to announce the 2nd major release of my R package for graph theory analysis of brain MRI data, "brainGraph".
The main page on CRAN is at:

The GitHub repository is at:

The latest version is already on CRAN for Linux distributions, and should be for Windows and Mac OS X soon (but there may be issues on non-Linux systems; see Chapter 1 of the User Guide).

To install directly from CRAN:
> install.packages('brainGraph')

In the meantime (and for development versions), you may install from GitHub using the R package "devtools":
> devtools::install_github('cwatson/brainGraph')

Getting help
The new User Guide has been completely overhauled, and now has a permanent link at: my GitHub Pages site (PDF warning). Please start at the "Preface".

You may also get help by opening an Issue on the GitHub repository, or join the Google Group.

New features
You can find the release notes/changelog in, at:

Major additions (since v1.0.0) that should be of interest include:

  • Vertex- and graph-level mediation analysis (chapter 11 of the Guide)
  • Multi-threshold permutation correction (MTPC) for GLM analyses (chapter 9)
  • Extension of GLM-based functions (including the network-based statistic [NBS] and MTPC) to allow for multiple contrasts in a single function call, and to allow for both T- and F-contrasts
  • Permutation/randomization is now done using the Freedman-Lane algorithm (as in randomise and PALM), although models are limited to simple GLM's
  • Introduction of R's S3 classes to simplify plotting and summarizing results
  • Calculation of a network's s-core membership
  • Calculation of network communicability and vertex communicability betweenness centrality

Please let me know if you have any issues, bug reports, feature requests, etc.

Chris Watson