Rapoport, R.; Greenberg, A.; Yakhini, Z.; Simon, I. A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms. Biology2024, 13, 175.
Rapoport, R.; Greenberg, A.; Yakhini, Z.; Simon, I. A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms. Biology 2024, 13, 175.
Rapoport, R.; Greenberg, A.; Yakhini, Z.; Simon, I. A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms. Biology2024, 13, 175.
Rapoport, R.; Greenberg, A.; Yakhini, Z.; Simon, I. A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms. Biology 2024, 13, 175.
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, H3K9me3 and H3K27me3 large domains, HiC compartments and lamina associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNAs) 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.
Keywords
Gene set enrichment analysis (GSEA); GO annotations; spatial dependencies; cyclic permutation; replication timing; copy number alterations (CNA)
Subject
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
