ArticleNucleic acids research2013
PGMRA: a web server for (phenotype x genotype) many-to-many relation analysis in GWAS.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Multi-Omic Bicluster Association Analysis (MOBAA)-a tool for identifying population subgroups with distinct multi-omics molecular profiles.Bioinformatics advances · 2026Article
- Subgrouping germinal center-derived B-cell lymphomas based on machine learning-deduced DNA methylation modules.Leukemia · 2025Article
- Gene expression networks regulated by human personality.Molecular psychiatry · 2024Review
- Temperament & Character account for brain functional connectivity at rest: A diathesis-stress model of functional dysregulation in psychosis.Molecular psychiatry · 2023Review
- Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods.Scientific reports · 2023Article
- miR-124-3p target genes identify globus pallidus role in suicide ideation recovery in borderline personality disorder.Npj mental health research · 2023Article
- Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture.Cardiovascular diabetology · 2022Article
- Advancing the use of genome-wide association studies for drug repurposing.Nature reviews. Genetics · 2021Review
- Three genetic-environmental networks for human personality.Molecular psychiatry · 2021Article
- Uncovering the complex genetics of human character.Molecular psychiatry · 2020Article
- Uncovering the complex genetics of human temperament.Molecular psychiatry · 2020Article
- Article
- The complex genetics and biology of human temperament: a review of traditional concepts in relation to new molecular findings.Translational psychiatry · 2019Review
- It is time to apply biclustering: a comprehensive review of biclustering applications in biological and biomedical data.Briefings in bioinformatics · 2019Review
- What is the natural measurement unit of temperament: single traits or profiles?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Review
- Parkinsonian motor impairment predicts personality domains related to genetic risk and treatment outcomes in schizophrenia.NPJ schizophrenia · 2017Article
- The influence of temperament and character profiles on specialty choice and well-being in medical residents.PeerJ · 2016Article
- NMF-mGPU: non-negative matrix factorization on multi-GPU systems.BMC bioinformatics · 2015Article
- Uncovering the hidden risk architecture of the schizophrenias: confirmation in three independent genome-wide association studies.The American journal of psychiatry · 2015Article
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Authors and funding
7 authors.
Funding
Abstract
It has been proposed that single nucleotide polymorphisms (SNPs) discovered by genome-wide association studies (GWAS) account for only a small fraction of the genetic variation of complex traits in human population. The remaining unexplained variance or missing heritability is thought to be due to marginal effects of many loci with small effects and has eluded attempts to identify its sources. Combination of different studies appears to resolve in part this problem. However, neither individual GWAS nor meta-analytic combinations thereof are helpful for disclosing which genetic variants contribute to explain a particular phenotype. Here, we propose that most of the missing heritability is latent in the GWAS data, which conceals intermediate phenotypes. To uncover such latent information, we propose the PGMRA server that introduces phenomics--the full set of phenotype features of an individual--to identify SNP-set structures in a broader sense, i.e. causally cohesive genotype-phenotype relations. These relations are agnostically identified (without considering disease status of the subjects) and organized in an interpretable fashion. Then, by incorporating a posteriori the subject status within each relation, we can establish the risk surface of a disease in an unbiased mode. This approach complements-instead of replaces-current analysis methods. The server is publically available at http://phop.ugr.es/fenogeno.
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