A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms

Rachel Rapoport*, Avraham Greenberg, Zohar Yakhini, Itamar Simon*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes’ spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, large H3K9me3 and H3K27me3 domains, HiC compartments and lamina-associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNA) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.

Original languageAmerican English
Article number175
JournalBiology
Volume13
Issue number3
DOIs
StatePublished - Mar 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Keywords

  • copy number alterations (CNA)
  • cyclic permutation
  • gene set enrichment analysis (GSEA)
  • GO annotations
  • replication timing
  • spatial dependencies

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