ArticleBMC bioinformatics2022
Detecting gene-gene interactions from GWAS using diffusion kernel principal components.
Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Turning heterogeneity of statistical epistasis networks to an advantage.Briefings in bioinformatics · 2026Article
- Bioinformatics in crop research: using genomic data for crop improvement.Frontiers in plant science · 2026Review
- Understanding and applying gene-environment interactions: a guide for nutrition professionals with an emphasis on integration in African research settings.Nutrition reviews · 2025Review
- MR-GGI: accurate inference of gene-gene interactions using Mendelian randomization.BMC bioinformatics · 2024Article
- netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity.Frontiers in genetics · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genes and gene products do not function in isolation but as components of complex networks of macromolecules through physical or biochemical interactions. Dependencies of gene mutations on genetic background (i.e., epistasis) are believed to play a role in understanding molecular underpinnings of complex diseases such as inflammatory bowel disease (IBD). However, the process of identifying such interactions is complex due to for instance the curse of high dimensionality, dependencies in the data and non-linearity. Here, we propose a novel approach for robust and computationally efficient epistasis detection. We do so by first reducing dimensionality, per gene via diffusion kernel principal components (kpc). Subsequently, kpc gene summaries are used for downstream analysis including the construction of a gene-based epistasis network. We show that our approach is not only able to recover known IBD associated genes but also additional genes of interest linked to this difficult gastrointestinal disease.
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