ArticleBMC bioinformatics2012
Core Hunter II: fast core subset selection based on multiple genetic diversity measures using Mixed Replica search.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- Uncovering the historic genetic diversity of Ugandan Robusta coffee germplasm: a foundation for core collection design.BMC plant biology · 2026Article
- Ancient grains illuminate the mosaic origin of domesticated wheat.Nature plants · 2026Article
- Development of user-selectable diverse sets of cultivated and wild soybean germplasm for genetic and breeding applications.The plant genome · 2026Article
- Development and application of core collection, KASP markers and SNP-based DNA fingerprinting inFrontiers in plant science · 2026Article
- Genetic Diversity and Construction of Salt-Tolerant Core Germplasm in Maize (Plants (Basel, Switzerland) · 2025Article
- Genetic Diversity Analysis and Core Germplasm Collection Construction of Tartary Buckwheat Based on SSR Markers.Plants (Basel, Switzerland) · 2025Article
- Genetic Diversity Analysis and Core Collection Construction of AncientInternational journal of molecular sciences · 2024Article
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- Genome analyses reveal population structure and a purple stigma color gene candidate in finger millet.Nature communications · 2023Article
- Genetic Diversity Analysis and Core Germplasm Collection Construction of Radish Cultivars Based on Structure Variation Markers.International journal of molecular sciences · 2023Article
- Identification of superior parents with high fiber quality using molecular markers and phenotypes based on a core collection of upland cotton (Molecular breeding : new strategies in plant improvement · 2022Article
- Graph-based pan-genome reveals structural and sequence variations related to agronomic traits and domestication in cucumber.Nature communications · 2022Article
- Genome-wide approaches delineate the additive, epistatic, and pleiotropic nature of variants controlling fatty acid composition in peanut (Arachis hypogaea L.).G3 (Bethesda, Md.) · 2022Article
- CGIAR Barley Breeding Toolbox: A diversity panel to facilitate breeding and genomic research in the developing world.Frontiers in plant science · 2022Article
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- The MultisitePlant physiology · 2020Article
- Marker association study of yield attributing traits in common bean (Phaseolus vulgaris L.).Molecular biology reports · 2020Article
- ddRAD sequencing-based genotyping for population structure analysis in cultivated tomato provides new insights into the genomic diversity of Mediterranean 'da serbo' type long shelf-life germplasm.Horticulture research · 2020Article
- Article
- Core set construction and association analysis of Pinus massoniana from Guangdong province in southern China using SLAF-seq.Scientific reports · 2019Article
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4 authors.
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Abstract
backgroundSampling core subsets from genetic resources while maintaining as much as possible the genetic diversity of the original collection is an important but computationally complex task for gene bank managers. The Core Hunter computer program was developed as a tool to generate such subsets based on multiple genetic measures, including both distance measures and allelic diversity indices. At first we investigate the effect of minimum (instead of the default mean) distance measures on the performance of Core Hunter. Secondly, we try to gain more insight into the performance of the original Core Hunter search algorithm through comparison with several other heuristics working with several realistic datasets of varying size and allelic composition. Finally, we propose a new algorithm (Mixed Replica search) for Core Hunter II with the aim of improving the diversity of the constructed core sets and their corresponding generation times.
resultsOur results show that the introduction of minimum distance measures leads to core sets in which all accessions are sufficiently distant from each other, which was not always obtained when optimizing mean distance alone. Comparison of the original Core Hunter algorithm, Replica Exchange Monte Carlo (REMC), with simpler heuristics shows that the simpler algorithms often give very good results but with lower runtimes than REMC. However, the performance of the simpler algorithms is slightly worse than REMC under lower sampling intensities and some heuristics clearly struggle with minimum distance measures. In comparison the new advanced Mixed Replica search algorithm (MixRep), which uses heterogeneous replicas, was able to sample core sets with equal or higher diversity scores than REMC and the simpler heuristics, often using less computation time than REMC.
conclusionThe REMC search algorithm used in the original Core Hunter computer program performs well, sometimes leading to slightly better results than some of the simpler methods, although it doesn't always give the best results. By switching to the new Mixed Replica algorithm overall results and runtimes can be significantly improved. Finally we recommend including minimum distance measures in the objective function when looking for core sets in which all accessions are sufficiently distant from each other. Core Hunter II is freely available as an open source project at http://www.corehunter.org.
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