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BrainSABER, transcriptomic, BrainSpan, RNA, brain


The Allen Brain Institute has used RNA sequencing and microarray technologies to sample the transcriptome of the developing human brain across sixteen cortical and subcortical regions for an age range of 8 weeks post conception through 40 years of age. The BrainSpan project is intended to give a baseline for the normal transcriptomic landscape of the human brain and is accompanied by a web interface that allows for the visualization of gene expression across brain ages and regions as well as differential comparisons between the sample sets. However, the current implementation does not allow for similarity assessment between user data and the BrainSpan dataset. To facilitate comparisons with outside user data, we developed the BrainSABER R package and Shiny web application. The BrainSABER package was designed to provide the user with a self-validating container for transcriptomic data, calculate the transcriptomic similarity between user data and the BrainSpan dataset across developmental ages and brain regions, and display the results using static and dynamic graphs. This package is split into a command-line accessible workflow for greater customization and a Shiny web application for ease of use. The command-line workflow utilizes Euclidean and cosine distances to evaluate similarity across all genes and the Shiny application evaluates cosine distance, Kendall’s Tau, and Spearman’s Rho for the 5000 genes with the highest stabilized variance across the BrainSpan dataset. Results are displayed as exportable static and dynamic heatmaps. Both Shiny and command-line workflows were self-validated as well as used for the secondary evaluation of samples from patients with atypical teratoid rhabdoid tumors (ATRT). The command-line BrainSABER package is available on Bioconductor (DOI: 10.18129/B9.bioc.BrainSABER), and the Shiny application can be accessed on the developmental “dev” branch of the bicbioeng/BrainSABER project on GitHub. This project was previously presented at the Bioc2020 conference (

First Advisor

Etienne Gnimpieba

Research Area

Biomedical Engineering