Genomic prediction for quantitative traits using kernel methods and whole genome sequence based approaches

Bibliographic Details
Druckausg.: Ober, Ulrike, Genomic prediction for quantitative traits, 2012, x,152 S.
Authors and Corporations: Ober, Ulrike
Title: Genomic prediction for quantitative traits using kernel methods and whole genome sequence based approaches vorgelegt von Ulrike Ober
Dissertation Note:Göttingen, Univ., Diss., 2012
published:
2012
Physical Description:Online-Ressource (PDF-Datei: 162 S., 4.954 KB)
Summary:Predicting genetic values is important in animal and plant breeding, personalized medicine and evolutionary biology. Traditionally, prediction is based on a best linear unbiased prediction (BLUP) approach within a linear mixed model framework, with covariance structures obtained from relationship measures between individuals. Nowadays, single nucleotide polymorphism (SNP) data allow to incorporate genomic information into the model (genomic BLUP (GBLUP)). Prediction is also the principal topic in geostatistics in the framework of correlated data. Here, the so-called krigingʺ approach performs BLUP using parameterized covariance functions. In this thesis, the kriging concept to perform genomic prediction using the family of Matérn covariance functions is adopted and kriging is compared to GBLUP in a whole-genome simulation study. The results of the simulation study suggest that kriging is superior over GBLUP in non-additive gene-action scenarios ...
Type of Resource:E-Book Thesis Hochschulschrift
Source:Verbunddaten SWB
Lizenzfreie Online-Ressourcen
Notes:Sprache der Zusammenfassung: Englisch
Language: English