Document Detail


Genomic selection for adjacent genetic markers of yorkshire pigs using regularized regression approaches.
MedLine Citation:
PMID:  25358359     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.
Authors:
Minsu Park; Tae-Hun Kim; Eun-Seok Cho; Heebal Kim; Hee-Seok Oh
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Asian-Australasian journal of animal sciences     Volume:  27     ISSN:  1011-2367     ISO Abbreviation:  Asian-australas. J. Anim. Sci.     Publication Date:  2014 Dec 
Date Detail:
Created Date:  2014-10-31     Completed Date:  2014-10-31     Revised Date:  2014-11-05    
Medline Journal Info:
Nlm Unique ID:  9884245     Medline TA:  Asian-Australas J Anim Sci     Country:  Korea (South)    
Other Details:
Languages:  eng     Pagination:  1678-83     Citation Subset:  -    
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