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MAGICC vertex-level gene expression data

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posted on 2024-01-09, 14:33 authored by Konrad WagstylKonrad Wagstyl, Sophie AdlerSophie Adler, Simon Vandekar, Jakob SeidlitzJakob Seidlitz, Travis T. Mallard, Richard Dear, Alex R. DeCasien, Theodore D. Satterthwaite, Siyuan Liu, Petra VertesPetra Vertes, Russel T. Shinohara, Aaron Alexander-Bloch, Daniel H. Geschwind, Armin Raznahan

Vertex-level expression data from the Multiscale Atlas of Gene Expression for Integrative Cortical Cartography

Files include:

Template cortical surface meshes for flat, inflated and very_inflated surfaces with 32k vertices

fs_LR.32k.L.flat.surf.gii

fs_LR.32k.L.inflated.surf.gii

fs_LR.32k.L.very_inflated.surf.gii

Glasser_2016.32k.L.label.gii - parcellation of fs_LR 32k surface according to Glasser et al., 2016 Nature.

ahba_vertex.npy - Atlas of cortical gene expression for 20,781 genes at 32k vertex locations

ahba_vertex_gradients.npy - Atlas of cortical gene expression gradients for 20,781 genes at 32k vertex locations

SuppTable2.csv - Gene-level characterisations for 20,781 in the same order as the above files. Includes gene symbol, alongside many other annotations described in the manuscript.

Example to code to analyse these data can be found at:
https://github.com/kwagstyl/magicc

Funding

Deep Learning of Cerebral Cortex Microstructure

Wellcome Trust

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