Evidence map›Paper›PMID 38534445›Full record

ArticleBiology2024

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

Rachel Rapoport, Avraham Greenberg, Zohar Yakhini, Itamar Simon

Abstract read
In one paragraph

Article in Biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Rachel RapoportMicrobiology and Molecular Genetics, Hebrew University of Jerusalem-IMRIC, Jerusalem 9112102, Israel.
Avraham GreenbergMicrobiology and Molecular Genetics, Hebrew University of Jerusalem-IMRIC, Jerusalem 9112102, Israel.
Zohar YakhiniEfi Arazi School of Computer Science, Reichman University (IDC Herzliya), Herzliya 4610101, Israel.
Itamar SimonMicrobiology and Molecular Genetics, Hebrew University of Jerusalem-IMRIC, Jerusalem 9112102, Israel.ORCID 0000-0002-8517-1903

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

copy number alterations (CNA)cyclic permutationgene set enrichment analysis (GSEA)GO annotationsreplication timingspatial dependencies

Identifiers

PMID38534445
PMCPMC10967837

What Socratic holds

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LicenceCC BY
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Registered trials

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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.