ArticlePlant methods2023
ShinyCore: An R/Shiny program for establishing core collection based on single nucleotide polymorphism data.
Article in Plant methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- A tomato MAGIC population reveals candidate genes for leaf dry matter and phenolics, two key traits for stress resilience and climate-smart breeding.Frontiers in plant science · 2026Article
- Methods for the Construction of Core Collections Using SNP Markers.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Developing a core collection for the conservation of Theobroma cacao's genetic diversity.BMC genomics · 2025Article
- CountrywideFrontiers in plant science · 2025Article
- Optimizing core collections for genetic studies: a worldwide flax germplasm case study.Frontiers in plant science · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundManaging and investigating all available genetic resources are challenging. As an alternative, breeders and researchers use core collection-a representative subset of the entire collection. A good core is characterized by high genetic diversity and low repetitiveness. Among the several available software, GenoCore uses a coverage criterion that does not require computationally expensive distance-based metrics.
resultsShinyCore is a new method to select a core collection through two phases. The first phase uses the coverage criterion to quickly attain a fixed coverage, and the second phase uses a newly devised score (referred to as the rarity score) to further enhance diversity. It can attain a fixed coverage faster than a currently available algorithm devised for the coverage criterion, so it will benefit users who have big data. ShinyCore attains the minimum coverage specified by a user faster than GenoCore, and it then seeks to add entries with the rarest allele for each marker. Therefore, measures of genetic diversity and distance can be improved.
conclusionAlthough GenoCore is a fast algorithm, its implementation is difficult for those unfamiliar with R, ShinyCore can be easily implemented in Shiny with RStudio and an interactive web applet is available for those who are not familiar with programming languages.
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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.