ArticleScientific reports2020
GMStool: GWAS-based marker selection tool for genomic prediction from genomic data.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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38 citing papers in PubMed.
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- Integrative genomic approaches to unravel genomic regions and candidate genes associated with flag leaf photosynthesis at the reproductive stage in rice.Frontiers in plant science · 2026Article
- Multi-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp.Scientific reports · 2025Article
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- Variable selection strategies for genomic prediction of growth and carcass related traits in experimental Nellore cattle herds under different selection criteria.Scientific reports · 2025Article
- Genome-Wide Association Analysis and Genomic Selection for Growth Traits in Grass Carp (Animals : an open access journal from MDPI · 2025Article
- Comparison of genomic prediction accuracies in dairy cattle lactation traits using five classes of functional variants versus generic SNP.Genetics, selection, evolution : GSE · 2025Article
- Metabolic marker-assisted genomic prediction improves hybrid breeding.Plant communications · 2025Article
- Exploring genetic variants affecting milk production traits through genome-wide association study in Vrindavani crossbred cattle of India.Tropical animal health and production · 2025Article
- Enhancing Genomic Prediction Accuracy of Reproduction Traits in Rongchang Pigs Through Machine Learning.Animals : an open access journal from MDPI · 2025Article
- Mutual information-based best linear unbiased prediction for enhanced genomic prediction accuracy.Journal of animal science · 2025Article
- Beyond the genome: the role of functional markers in contemporary plant breeding.Frontiers in plant science · 2025Review
- GPOSYSH: Genomic Prediction ofRecent advances in food, nutrition & agriculture · 2025Article
- Integrating multi-layered biological priors to improve genomic prediction accuracy in beef cattle.Biology direct · 2024Article
- Review of applications of artificial intelligence (AI) methods in crop research.Journal of applied genetics · 2024Review
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3 authors.
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Abstract
The increased accessibility to genomic data in recent years has laid the foundation for studies to predict various phenotypes of organisms based on the genome. Genomic prediction collectively refers to these studies, and it estimates an individual's phenotypes mainly using single nucleotide polymorphism markers. Typically, the accuracy of these genomic prediction studies is highly dependent on the markers used; however, in practice, choosing optimal markers with high accuracy for the phenotype to be used is a challenging task. Therefore, we present a new tool called GMStool for selecting optimal marker sets and predicting quantitative phenotypes. The GMStool is based on a genome-wide association study (GWAS) and heuristically searches for optimal markers using statistical and machine-learning methods. The GMStool performs the genomic prediction using statistical and machine/deep-learning models and presents the best prediction model with the optimal marker-set. For the evaluation, the GMStool was tested on real datasets with four phenotypes. The prediction results showed higher performance than using the entire markers or the GWAS-top markers, which have been used frequently in prediction studies. Although the GMStool has several limitations, it is expected to contribute to various studies for predicting quantitative phenotypes. The GMStool written in R is available at www.github.com/JaeYoonKim72/GMStool .
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