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Updated: Sep 25, 2025

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Published on: June 13, 2025

Integrating neuroimaging and gene expression data using the imaging transcriptomics toolbox.

Alessio Giacomel¹, Daniel Martins¹, Matteo Frigo^2,3

¹Department of Neuroimaging, IoPPN, King's College London, London, UK.

|April 28, 2022

Summary

This summary is machine-generated.

This study introduces the Imaging Transcriptomics toolbox, a new command-line package for analyzing gene expression patterns related to neuroimaging phenotypes. It facilitates biological interpretation through gene set enrichment analyses.

Keywords:

Bioinformatics Computer sciences Health Sciences Neuroscience Sequence analysis

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Area of Science:

Neuroscience
Bioinformatics
Genomics

Background:

Integrating neuroimaging and transcriptomics data (Imaging Transcriptomics) is a growing field.
Standardized workflows for this integration are currently lacking.
This presents a challenge for researchers aiming to link brain structure/function with gene expression.

Purpose of the Study:

To introduce a new software package, the Imaging Transcriptomics toolbox.
To provide a standardized, user-friendly pipeline for imaging transcriptomics analysis.
To enable the identification of gene expression patterns correlated with neuroimaging phenotypes.

Main Methods:

Development of a command-line interface (CLI) package.
Implementation of a full imaging transcriptomics pipeline.
Integration of gene expression data with neuroimaging phenotypes.
Inclusion of gene set enrichment analysis for biological interpretation.

Main Results:

The Imaging Transcriptomics toolbox provides a standardized workflow.
Users can identify correlations between gene expression patterns and neuroimaging phenotypes.
The toolbox supports biological interpretation via gene set enrichment analysis.

Conclusions:

The Imaging Transcriptomics toolbox offers a valuable resource for researchers.
It simplifies the complex process of integrating neuroimaging and transcriptomics data.
This facilitates deeper biological insights into brain function and disease.