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BrainNetTest: Hypothesis Testing for Populations of Brain Networks

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.

Version: 0.2.0
Depends: R (≥ 4.0.0)
Imports: stats, graphics, igraph
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-04-23
DOI: 10.32614/CRAN.package.BrainNetTest
Author: Maximiliano Martino ORCID iD [aut, cre], Daniel Fraiman ORCID iD [aut]
Maintainer: Maximiliano Martino <maxii.martino at gmail.com>
BugReports: https://github.com/mmaximiliano/BrainNetTest/issues
License: MIT + file LICENSE
URL: https://github.com/mmaximiliano/BrainNetTest
NeedsCompilation: no
Materials: NEWS
CRAN checks: BrainNetTest results

Documentation:

Reference manual: BrainNetTest.html , BrainNetTest.pdf
Vignettes: Generating and Analyzing Brain Networks with Community Structures (source, R code)
Introduction to BrainNetTest (source, R code)

Downloads:

Package source: BrainNetTest_0.2.0.tar.gz
Windows binaries: r-release: BrainNetTest_0.2.0.zip, r-oldrel: BrainNetTest_0.2.0.zip
macOS binaries: r-release (arm64): BrainNetTest_0.2.0.tgz, r-oldrel (arm64): BrainNetTest_0.2.0.tgz, r-release (x86_64): BrainNetTest_0.2.0.tgz, r-oldrel (x86_64): BrainNetTest_0.2.0.tgz
Old sources: BrainNetTest archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.