Evidence map›Paper›PMID 33976144›Full record

ArticleNature communications2021

Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data.

Ben D Fulcher, Aurina Arnatkeviciute, Alex Fornito

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 3 pooled it
10.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

100 citing papers in PubMed, 3 syntheses or guidelines pooled it, 169 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Diffusion MRI reveals amyloid plaque-associated cellular signatures through spatial transcriptomic integration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  13. A data-driven framework linking the connectome to spatial gene expression gradients inspired by chemoaffinity theory.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  17. HyperpolarizedImaging neuroscience (Cambridge, Mass.) · 2026
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40 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Ben D FulcherSchool of Physics, The University of Sydney, Camperdown, NSW, Australia. ben.fulcher@sydney.edu.au.ORCID http://orcid.org/0000-0002-3003-4055
Aurina ArnatkeviciuteThe Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.
Alex FornitoThe Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.ORCID http://orcid.org/0000-0003-0866-3477
Monash University · AUThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptomic atlases have improved our understanding of the correlations between gene-expression patterns and spatially varying properties of brain structure and function. Gene-category enrichment analysis (GCEA) is a common method to identify functional gene categories that drive these associations, using gene-to-category annotation systems like the Gene Ontology (GO). Here, we show that applying standard GCEA methodology to spatial transcriptomic data is affected by substantial false-positive bias, with GO categories displaying an over 500-fold average inflation of false-positive associations with random neural phenotypes in mouse and human. The estimated false-positive rate of a GO category is associated with its rate of being reported as significantly enriched in the literature, suggesting that published reports are affected by this false-positive bias. We show that within-category gene-gene coexpression and spatial autocorrelation are key drivers of the false-positive bias and introduce flexible ensemble-based null models that can account for these effects, made available as a software toolbox.

Indexed as

Gene OntologyAnimalsBrainGene Expression ProfilingHumansMaleMiceMice, Inbred C57BLMolecular Sequence AnnotationReproducibility of ResultsSoftware

Identifiers

PMID33976144
PMCPMC8113439
OpenAlexW3160541163

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.