Decoding the chain from genes to cognition requires detailed insights into how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas (© 2015 Allen Institute for Brain Science) contains regional gene expression data, while the EBRAINS human brain atlas offers three-dimensional cytoarchitectonic maps reflecting the interindividual variability. JuGEx combines the analytical benefits of both repositories into a simple tool for integrating tissue transcriptome and probabilistic brain segregation.

  • Combine the analytical benefits of the comprehensive maps of the EBRAINS human brain atlas with the transcriptomics data offered by the Allen Brain Atlas
  • Choose to perform your analysis in Python, Matlab, or an intuitive graphical plugin of the EBRAINS Interactive Atlas Viewer

Tools


Transcriptomics meet cytoarchitecture

Differential gene expression analysis using EBRAINS human brain atlas

The principle of JuGEx is simple: Select two brain areas from the EBRAINS human brain atlas and a set of candidate genes of your interest. JuGEx will use probabilistic maps of brain regions to extract gene expression measurements from the Allen Brain Atlas (© 2015 Allen Institute for Brain Science), and perform a differential analysis of the genes and associated factors in the two brain regions. As a result, you obtain the computed p-values together with the extracted transcriptomics data, and can visually inspect the locations of the data samples in atlas reference space.

JuGEx is available to you in different forms: As a Matlab implementation, as a Python implementation included in the Brainscapes Python client, and as an interactive Plugin included in the EBRAINS Atlas Viewer, accessible from your browser right away. Choose the implementation that suits you the best.



References

Bludau S., Mühleisen T. W., Eickhoff, A. B., Hawrylycz M. J., Cichon S., Amunts K. (2018) Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network. Brain Structure and Function. https://doi.org/10.1007/s00429-018-1620-6

Access all EBRAINS services