ArticleBioData mining2022
Gene-Interaction-Sensitive enrichment analysis in congenital heart disease.
Article in BioData mining, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Neuro-Genomic Mapping of Cardiac Neurons with Systemic Analysis Reveals Cognitive and Neurodevelopmental Impacts in Congenital Heart Disease.Life (Basel, Switzerland) · 2025Article
- Systemic lupus erythematosus with high disease activity identification based on machine learning.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2023Article
- Nine quick tips for pathway enrichment analysis.PLoS computational biology · 2022Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundGene set enrichment analysis (GSEA) uses gene-level univariate associations to identify gene set-phenotype associations for hypothesis generation and interpretation. We propose that GSEA can be adapted to incorporate SNP and gene-level interactions. To this end, gene scores are derived by Relief-based feature importance algorithms that efficiently detect both univariate and interaction effects (MultiSURF) or exclusively interaction effects (MultiSURF*). We compare these interaction-sensitive GSEA approaches to traditional χ
resultsIn the simulation study and for both CTD datasets, both Relief-based approaches to GSEA captured more relevant and significant gene ontology terms compared to the univariate GSEA. Key terms and themes of interest include cell adhesion, migration, and signaling. A leading edge analysis highlighted semaphorins and their receptors, the Slit-Robo pathway, and other genes with roles in the secondary heart field and outflow tract development.
conclusionsOur results indicate that interaction-sensitive approaches to enrichment analysis can improve upon traditional univariate GSEA. This approach replicated univariate findings and identified additional and more robust support for the role of the secondary heart field and cardiac neural crest cell migration in the development of CTDs.
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Registered trials
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 OpenQuestion graph.