Standardizing workflows in imaging transcriptomics with the abagen toolbox
Abstract
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.
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Allen Institute Human Brain Atlas (AHBA)Allen Institute Human Brain Atlas (AHBA).
Article and author information
Author details
Funding
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.
Copyright
© 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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