Authors: A.I. Luppi, Z-Q. Liu, J.Y. Hansen, R. Cofre, M. Niu, E. Kuzmin, S. Froudist-Walsh, N. Palomero-Gallagher, & B. Misic.
This repository provides code to reproduce the main results of Luppi et al., "Benchmarking macaque brain gene expression for horizontal and vertical translation." Science Advances (2025, accepted) (preprint:).
It was developed in MATLAB 2019a by Andrea Luppi from the the Network Neuroscience Lab at the Montreal Neurological Institute, McGill University.
The study investigates the spatial correspondence of cortical patterns of gene expression in the macaque, against (i) protein density in the macaque cortex (vertical translation); and (ii) gene expression in the human cortex (horizontal translation).
This code relies on MATLAB code from the BrainSpace Toolbox for MATLAB by Vos de Wael et al. (2020) Communications Biology. The essential functions are included in this repo to ensure standalone functionality. For additional plotting functionality, also include in your MATLAB path the ENIGMA Toolbox by Lariviere et al. (2021) Nature Methods.
The original macaque cortical gene expression (stereo-seq) and cell type density data from Chen et al. (2023) Cell are available at https://macaque.digital-brain.cn/spatial-omics. The dataset is provided by the Brain Science Data Center, Chinese Academy of Sciences.
The original macaque receptor density data from Froudist-Walsh et al. (2023) Nature Neuroscience are available online on Ebrains.
The original macaque bulk RNA-seq gene expression data are available from the Supplementary Material of Bo et al. (2023) Nature Communications.
The original map of macaque intracortical myelination from T1w:T2w ratio is available on balsa.
The original macaque parvalbumin and calretinin density from immunohistochemistry and dendritic spine counts are available from the Supplementary Materials of Burt et al. (2018) Nature Neuroscience.
The main file is Luppi_macaque_brain_gene_translation_code_4GitHub.m This script should work out of the box, if run from the parent directory. To run, ensure you are in the main directory of the repo.
The data folder contains all the data you need to make this code run.
The utils folder contains support functions called by the main script, including some third-party code.