A practical guide to linking brain-wide gene expression and neuroimaging data

Aurina Arnatkevic̆iūtė, Ben D. Fulcher, Alex Fornito

Research output: Contribution to journalArticleResearchpeer-review

41 Citations (Scopus)

Abstract

The recent availability of comprehensive, brain-wide gene expression atlases such as the Allen Human Brain Atlas (AHBA) has opened new opportunities for understanding how spatial variations on molecular scale relate to the macroscopic neuroimaging phenotypes. A rapidly growing body of literature is demonstrating relationships between gene expression and diverse properties of brain structure and function, but approaches for combining expression atlas data with neuroimaging are highly inconsistent, with substantial variations in how the expression data are processed. The degree to which these methodological variations affect findings is unclear. Here, we outline a seven-step analysis pipeline for relating brain-wide transcriptomic and neuroimaging data and compare how different processing choices influence the resulting data. We suggest that studies using the AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field.

Original languageEnglish
Pages (from-to)353-367
Number of pages15
JournalNeuroImage
Volume189
DOIs
Publication statusPublished - 1 Apr 2019

Keywords

  • Allen human brain atlas
  • Connectome
  • Gene expression
  • Genetics
  • Genome
  • MRI
  • Transcriptome

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