Dear Dr. Robert, It hadn't occurred to me, as I am the sole developer of the package. The User Guide should have enough information to get started (so please check it out), but I might add some content to GitHub Pages with specific, tutorial-like information (as opposed to the documentation-style of the User Guide).
Chris
On Wed, Feb 7, 2018 at 6:00 AM, gabriel robert < gabriel.hadrien.robert@gmail.com> wrote:
Dear Dr Watson,
Many thanks for developping your toolbox,
Is there any project to propose any "courses" or anything related to courses to get started with your toolbox,
Best wishes,
Gabriel Robert, MD, PhD Rennes, France
2018-02-07 2:14 GMT+01:00 Chris Watson cwa135@alum.mit.edu:
Dear Freesurfer 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: https://cran.r-project.org/web /packages/brainGraph/index.html The GitHub repository is at: https://github.com/cwatson/brainGraph
*Installation* 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) https://cwatson.github.io/files/brainGraph_UserGuide.pdf. Please start at the "Preface".
You may also get help by opening an Issue https://github.com/cwatson/brainGraph/issues on the GitHub repository, or join the Google Group https://groups.google.com/forum/?hl=en#%21forum/brainGraph-help.
*New features* You can find the release notes/changelog in NEWS.md, at: https://github.com/cwatson/brainGraph/blob/master/NEWS.md
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
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