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Standardizing workflows in imaging transcriptomics with the abagen toolbox

  1. Ross D Markello  Is a corresponding author
  2. Aurina Arnatkevičiūtė
  3. Jean-Baptiste Poline
  4. Ben D Fulcher
  5. Alex Fornito
  6. Bratislav Misic  Is a corresponding author
  1. McGill University, Canada
  2. Monash University, Australia
  3. University of Sydney, Australia
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Cite this article as: eLife 2021;10:e72129 doi: 10.7554/eLife.72129


Gene expression fundamentally shapes the structural and functional architecture of the human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack of standardization across research groups has given rise to myriad processing pipelines for using these data. Here, we develop the abagen toolbox, an open-access software package for working with transcriptomic data, and use it to examine how methodological variability influences the outcomes of research using the Allen Human Brain Atlas. Applying three prototypical analyses to the outputs of 750,000 unique processing pipelines, we find that choice of pipeline has a large impact on research findings, with parameters commonly varied in the literature influencing correlations between derived gene expression and other imaging phenotypes by as much as p ≥ 1:0. Our results further reveal an ordering of parameter importance, with processing steps that influence gene normalization yielding the greatest impact on downstream statistical inferences and conclusions. The presented work and the development of the abagen toolbox lay the foundation for more standardized and systematic research in imaging transcriptomics, and will help to advance future understanding of the influence of gene expression in the human brain.

Data availability

All datasets used in this study are publicly available. Detailed information about the datasets and how to access them are described in the manuscript.

The following previously published data sets were used

Article and author information

Author details

  1. Ross D Markello

    McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
    For correspondence
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1057-1336
  2. Aurina Arnatkevičiūtė

    Monash University, Clayton, Australia
    Competing interests
    No competing interests declared.
  3. Jean-Baptiste Poline

    Montreal Neurological Institute & Hospital,, McGill University, Montreal, QC, Canada, Canada
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9794-749X
  4. Ben D Fulcher

    School of Physics, University of Sydney, Sydney, Australia
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3003-4055
  5. Alex Fornito

    Monash University, Clayton, Australia
    Competing interests
    Alex Fornito, Reviewing editor, eLife.
  6. Bratislav Misic

    McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
    For correspondence
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0307-2862


Natural Sciences and Engineering Research Council of Canada (017-04265)

  • Bratislav Misic

National Health and Medical Research Council (3274306)

  • Alex Fornito

National Institutes of Health (NIH-NIBIB P41 EB019936)

  • Jean-Baptiste Poline

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Saad Jbabdi, University of Oxford, United Kingdom

Publication history

  1. Received: July 12, 2021
  2. Accepted: November 15, 2021
  3. Accepted Manuscript published: November 16, 2021 (version 1)


© 2021, Markello et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.


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