BrainSuite Statistics Toolbox in R

The BrainSuite Statistics Toolbox in R (bstr) is a software package developed in R that performs statistical analysis of population-level neuroimaging data processed using BrainSuite. It provides statistical tools for conducting cortical thickness analysis, tensor based morphometry, and analysis of diffusion measures.

Bstr is cross-platform and is available on macOS, Windows,and Linux based systems (all platforms with R support). bstr is distributed under an open source license (GPLv2)). It supports functionality for automated report generation to visualize statistical results using R-shiny and R markdown. The volumetric analysis report contains the cluster table, visualizations of clusters on image slices, and shows both the unadjusted and the adjusted versions of p-values and t statistics, respectively. The ROI analysis report shows the demographic spreadsheet, automatic bar plots for ANOVA and regressions, and scatter plot for correlation analyses. bstr also exports an R markdown report that contains reproducible R commands in both the Rmd file and in the html document. This enables complete reproducibility of statistical results and only requires packaging the R markdown file along with the data.

Development Team

The lead developer for bstr is Shantanu Joshi at the Ahmanson-Lovelace Brain Mapping Center at UCLA. The project is supervised by David Shattuck, with contributions from Yeun Kim, Kayla Schroeder, and Anand Joshi. Change all the websites to direct home pages

The bstr toolkit is a part of BrainSuite, an open-source software project that is produced and distributed as a collaborative effort led by David Shattuck at UCLA and Richard Leahy at the Biomedical Imaging Group at the University of Southern California. Major contributors to the BrainSuite project include Chitresh Bhushan, Soyoung Choi, Hanna Damasio, Justin P. Haldar, Anand A. Joshi, Shantanu H. Joshi, Yeun Kim, Divya Varadarajan, and Jessica L. Wisnowski.


For questions or support, please email us at You can also submit issues to our issue tracker on Github.


# reproducepaper