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BrainNetTest  

Hypothesis Testing for Populations of Brain Networks
View on CRAN: Click here


Download and install BrainNetTest package within the R console
Install from CRAN:
install.packages("BrainNetTest")

Install from Github:
library("remotes")
install_github("cran/BrainNetTest")

Install by package version:
library("remotes")
install_version("BrainNetTest", "0.2.0")



Attach the package and use:
library("BrainNetTest")
Maintained by
Maximiliano Martino
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-21
Latest Update: 2026-04-23
Description:
Non-parametric hypothesis testing for populations of brain networks represented as graphs, following the L1-distance ANOVA framework of Fraiman and Fraiman (2018) <doi:10.1038/s41598-018-21688-0>. The package builds on this nonparametric graph-comparison framework, extending it with procedures for edge-level inference and identification of the specific connections driving group differences. In particular, it provides utilities to compute central (mean) graphs, pairwise Manhattan distances between adjacency matrices, the group test statistic T, and a fast permutation procedure to identify the critical edges that drive between-group differences. Helper functions to generate synthetic community-structured graphs and to visualise brain networks with communities are also included.
How to cite:
Maximiliano Martino (2026). BrainNetTest: Hypothesis Testing for Populations of Brain Networks. R package version 0.2.0, https://cran.r-project.org/web/packages/BrainNetTest. Accessed 11 Sep. 2026.
Previous versions and publish date:
0.1.0 (2026-04-21 22:52), 0.2.0 (2026-04-23 18:30), (2026-07-09 07:59)
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Complete documentation for BrainNetTest
Functions, R codes and Examples using the BrainNetTest R package
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