ArticleFrontiers in genetics2019
Multi-Phenotype Association Decomposition: Unraveling Complex Gene-Phenotype Relationships.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Type Genomics: A Framework for Integrating Genomic Data into Biodiversity and Taxonomic Research.Systematic biology · 2025Guideline
- Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals.Nature communications · 2021Pooled it
- Epistasis and pleiotropy-induced variation for plant breeding.Plant biotechnology journal · 2024Review
- Rapid screening of secondary aromatic metabolites in Populus trichocarpa leaves.Biotechnology for biofuels and bioproducts · 2023Article
- The Promises, Challenges, and Opportunities of Omics for Studying the Plant Holobiont.Microorganisms · 2022Article
- mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights.Metabolites · 2022Article
- A multi-trait multi-locus stepwise approach for conducting GWAS on correlated traits.The plant genome · 2022Article
- Deciphering Pleiotropic Signatures of Regulatory SNPs inInternational journal of molecular sciences · 2022Article
- Understanding the metabolome and metagenome as extended phenotypes: The next frontier in macroalgae domestication and improvement.Journal of the World Aquaculture Society · 2021Article
- Breeding for Climate Change Resilience: A Case Study of Loblolly Pine (Frontiers in plant science · 2021Review
- Multi-trait multi-locus SEM model discriminates SNPs of different effects.BMC genomics · 2020Article
- Genome-Wide Association Study of Wood Anatomical and Morphological Traits inFrontiers in plant science · 2020Article
- Data Integration in Poplar: 'Omics Layers and Integration Strategies.Frontiers in genetics · 2019Review
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Various patterns of multi-phenotype associations (MPAs) exist in the results of Genome Wide Association Studies (GWAS) involving different topologies of single nucleotide polymorphism (SNP)-phenotype associations. These can provide interesting information about the different impacts of a gene on closely related phenotypes or disparate phenotypes (pleiotropy). In this work we present MPA Decomposition, a new network-based approach which decomposes the results of a multi-phenotype GWAS study into three bipartite networks, which, when used together, unravel the multi-phenotype signatures of genes on a genome-wide scale. The decomposition involves the construction of a phenotype powerset space, and subsequent mapping of genes into this new space. Clustering of genes in this powerset space groups genes based on their detailed MPA signatures. We show that this method allows us to find multiple different MPA and pleiotropic signatures within individual genes and to classify and cluster genes based on these SNP-phenotype association topologies. We demonstrate the use of this approach on a GWAS analysis of a large population of 882
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