ArticleBioinformatics advances2025
GeneSetPheno: a web application for the integration, summary, and visualization of gene and variant-phenotype associations across gene sets.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
4 authors.
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Abstract
Motivation: The comprehensive study of genotype-phenotype relationships requires the integration of multiple data types to "triangulate" signals and derive meaningful biological conclusions. Large-scale biobanks and public resources generate a wealth of comprehensive results, facilitating the discovery of associations between genes or genetic variants and multiple phenotypes. However, analyzing these data across resources presents several challenges, including limited flexibility in gene set analysis, the integration of multipe databases, and the need for effective data visualization to aid interpretation. Results: GeneSetPheno is a user-friendly graphical interface that integrates, summarizes, and visualizes gene and variant-phenotype associations across genomic resources. It allows users to explore interrelationships between genetic variants and phenotypes, offering insights into the genetic factors driving phenotypic variation within user-defined gene sets. GeneSetPheno also supports comparisons across gene sets to identify shared or unique genetic variants, phenotypic associations, biological pathways, and potential gene-gene interactions. GeneSetPheno is a free and highly configurable tool for exploring the complex relationships between gene sets, genetic variants, and phenotypes. Target users include molecular biologists and clinicians who wish to explore a gene or gene set of particular interest. Availability and implementation: GeneSetPheno is freely accessible at: https://shiny.wehi.edu.au/han.ji/GeneSetPheno/. The source code is available on GitHub at: https://github.com/bahlolab/GeneSetPheno.
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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.