Record Details

Performance of Bayesian and BLUP alphabets for genomic prediction: analysis, comparison and results

KRISHI: Publication and Data Inventory Repository

View Archive Info
 
 
Field Value
 
Title Performance of Bayesian and BLUP alphabets for genomic prediction: analysis, comparison and results
Not Available
 
Creator Prabina Kumar Meher
Sachin Rustgi
Anuj Kumar
 
Subject Bayesian methods
BLUP
Estimated breeding value
 
Description Not Available
We evaluated the performances of three BLUP and five Bayesian methods for genomic prediction by using nine actual and 54 simulated datasets. The genomic prediction accuracy was measured using Pearson’s correlation coefficient between the genomic estimated breeding value (GEBV) and the observed phenotypic data using a fivefold cross-validation approach with 100 replications. The Bayesian alphabets performed better for the traits governed by a few genes/QTLs with relatively larger effects. On the contrary, the BLUP alphabets (GBLUP and CBLUP) exhibited higher genomic prediction accuracy for the traits controlled by several small-effect QTLs. Additionally, Bayesian methods performed better for the highly heritable traits and, for other traits, performed at par with the BLUP methods. Further, genomic BLUP (GBLUP) was identified as the least biased method for the GEBV estimation. Among the …
Not Available
 
Date 2022-05-26T08:36:17Z
2022-05-26T08:36:17Z
2022-05-04
 
Type Research Paper
 
Identifier Meher, P.K., Rustgi, S. & Kumar, A. (2022) Performance of Bayesian and BLUP alphabets for genomic prediction: analysis, comparison and results. Heredity (2022). https://doi.org/10.1038/s41437-022-00539-9
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/72398
 
Language English
 
Relation Not Available;
 
Publisher Nature Publishing Group