Predicting Genetic Values: A Kernel-Based Best Linear Unbiased Prediction With Genomic Data
نویسندگان
چکیده
منابع مشابه
Predicting Genetic Values: A Kernel-Based Best Linear Unbiased Prediction With Genomic Data
Genomic data provide a valuable source of information for modeling covariance structures, allowing a more accurate prediction of total genetic values (GVs). We apply the kriging concept, originally developed in the geostatistical context for predictions in the low-dimensional space, to the high-dimensional space spanned by genomic single nucleotide polymorphism (SNP) vectors and study its prope...
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BACKGROUND With the availability of high density whole-genome single nucleotide polymorphism chips, genomic selection has become a promising method to estimate genetic merit with potentially high accuracy for animal, plant and aquaculture species of economic importance. With markers covering the entire genome, genetic merit of genotyped individuals can be predicted directly within the framework...
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Genomic selection is an upgrading form of marker-assisted selection for quantitative traits, and it differs from the traditional marker-assisted selection in that markers in the entire genome are used to predict genetic values and the QTL detection step is skipped. Genomic selection holds the promise to be more efficient than the traditional marker-assisted selection for traits controlled by po...
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ژورنال
عنوان ژورنال: Genetics
سال: 2011
ISSN: 1943-2631
DOI: 10.1534/genetics.111.128694