ArticleBMC bioinformatics2018
WISH-R- a fast and efficient tool for construction of epistatic networks for complex traits and diseases.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Homozygosity Accumulated Through Genetic Drift and Inbreeding Underpins High Mutation Load in an Endangered Beluga Whale Population.Molecular ecology · 2026Article
- Evaluation of epistasis detection methods for quantitative phenotypes.Bioinformatics (Oxford, England) · 2026Article
- Exploring genome, transcriptome, and microbiome interactions related to feed efficiency and methane emissions in Bos indicus through multi-omics network analysis.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Distinct network patterns emerge from Cartesian and XOR epistasis models: a comparative network science analysis.BioData mining · 2024Article
- Distinct Network Patterns Emerge from Cartesian and XOR Epistasis Models: A Comparative Network Science Analysis.Research square · 2024Article
- Genome-Wide Epistatic Network Analyses of Semantic Fluency in Older Adults.International journal of molecular sciences · 2024Article
- NSPA: characterizing the disease association of multiple genetic interactions at single-subject resolution.Bioinformatics advances · 2023Article
- Article
- Roles of interacting stress-related genes in lifespan regulation: insights for translating experimental findings to humans.Journal of translational genetics and genomics · 2021Article
- Extensive haplotypes are associated with population differentiation and environmental adaptability in Upland cotton (Gossypium hirsutum).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Article
- Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs.Scientific reports · 2020Article
- Article
- Genome-Wide Epistatic Interaction Networks Affecting Feed Efficiency in Duroc and Landrace Pigs.Frontiers in genetics · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundGenetic epistasis is an often-overlooked area in the study of the genomics of complex traits. Genome-wide association studies are a useful tool for revealing potential causal genetic variants, but in this context, epistasis is generally ignored. Data complexity and interpretation issues make it difficult to process and interpret epistasis. As the number of interaction grows exponentially with the number of variants, computational limitation is a bottleneck. Gene Network based strategies have been successful in integrating biological data and identifying relevant hub genes and pathways related to complex traits. In this study, epistatic interactions and network-based analysis are combined in the Weighted Interaction SNP hub (WISH) method and implemented in an efficient and easy to use R package.
resultsThe WISH R package (WISH-R) was developed to calculate epistatic interactions on a genome-wide level based on genomic data. It is easy to use and install, and works on regular genomic data. The package filters data based on linkage disequilibrium and calculates epistatic interaction coefficients between SNP pairs based on a parallelized efficient linear model and generalized linear model implementations. Normalized epistatic coefficients are analyzed in a network framework, alleviating multiple testing issues and integrating biological signal to identify modules and pathways related to complex traits. Functions for visualizing results and testing runtimes are also provided.
conclusionThe WISH-R package is an efficient implementation for analyzing genome-wide epistasis for complex diseases and traits. It includes methods and strategies for analyzing epistasis from initial data filtering until final data interpretation. WISH offers a new way to analyze genomic data by combining epistasis and network based analysis in one method and provides options for visualizations. This alleviates many of the existing hurdles in the analysis of genomic interactions.
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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.