Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
11 05 2021
11 05 2021
Historique:
received:
30
11
2020
accepted:
31
03
2021
entrez:
12
5
2021
pubmed:
13
5
2021
medline:
2
6
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33976144
doi: 10.1038/s41467-021-22862-1
pii: 10.1038/s41467-021-22862-1
pmc: PMC8113439
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
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