ArticleBMC bioinformatics2014
solGS: a web-based tool for genomic selection.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Genomic Predicted cross performance: a tool for optimizing parental combinations in breeding programs.Database : the journal of biological databases and curation · 2025Article
- Genetic analysis of cassava brown streak disease root necrosis using image analysis and genome-wide association studies.Frontiers in plant science · 2024Article
- Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals.Genes · 2023Review
- Breedbase: a digital ecosystem for modern plant breeding.G3 (Bethesda, Md.) · 2022Article
- Current status and impending progress for cassava structural genomics.Plant molecular biology · 2022Review
- PANOMICS meets germplasm.Plant biotechnology journal · 2020Review
- Article
- Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia.Frontiers in plant science · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders.
resultsWe have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs.
conclusionssolGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.
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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.