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Showing 1 to 3 of 3 for “"ridge regression best linear unbiased prediction"”.

  1. Evaluation of genomic prediction models that incorporates peak GWAS signals in maize and sorghum diversity panels

    … panel in maize and one in sorghum using a Ridge Regression Best Linear Unbiased prediction (RR-BLUP) model that included fixed effect covariates tagging peak GWAS signals. The ability of such covariates to increase GS prediction accuracy in the RR-BLUP model under a wide variety of genetic …

    uiuc Repository record for Evaluation of genomic prediction models that incorporates peak GWAS signals in maize and sorghum diversity panels (opens in a new tab)

  2. Genomic Selection and Genome-Wide Association Study in Populus trichocarpa and Pinus taeda

    … taeda. GEBVs accuracies were estimated using a ridge regressionbest linear unbiased prediction (rrBLUP) model, and these accuracies were compared with estimated heritabilities. GWAS was also performed for the both imputed and non–imputed data of P. taeda population using TASSEL (Trait Analysis …

    vt Repository record for Genomic Selection and Genome-Wide Association Study in Populus trichocarpa and Pinus taeda (opens in a new tab)

  3. Testing new genetic and genomic approaches for trait mapping and prediction in wheat (Triticum aestivum) and rice (Oryza spp)

    … of the QTLs were detected by DArT markers alone. Prediction accuracies from the two marker platforms were mostly similar and largely dependent on trait genetic architecture. The second part of this thesis focused on MAGIC populations, which incorporate diversity and novel allelic combinations from …

    cambridge Repository record for Testing new genetic and genomic approaches for trait mapping and prediction in wheat (Triticum aestivum) and rice (Oryza spp) (opens in a new tab)