Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Bayes method for joint estimation of continuous traits and threshold traits based on genomic estimated breeding value

A technique for joint estimation and breeding value, applied in the Bayesian field, which can solve problems such as lack of joint analysis

Inactive Publication Date: 2016-10-12
INST OF ANIMAL HUSBANDRY & VETERINARY MEDICINE ANHUI ACAD OF AGRI SCI
View PDF3 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, joint analysis of continuous and threshold traits is lacking

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Bayes method for joint estimation of continuous traits and threshold traits based on genomic estimated breeding value
  • Bayes method for joint estimation of continuous traits and threshold traits based on genomic estimated breeding value
  • Bayes method for joint estimation of continuous traits and threshold traits based on genomic estimated breeding value

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0061] This example proposes a new Bayesian method based on the line-threshold model, called LT-BayesCπ, for joint analysis of continuous traits and threshold traits.

[0062] 1. Method

[0063] 1.1 Model

[0064] let y′ 1 ={y 1，i}(i=1,2,…,n) is the vector of observation values ​​of continuous traits, y′ 2 ={y 2，i}(i=1,2,…,n) is the threshold trait observation value vector, l′={l i}(i=1,2,...,n) is the latent variable vector associated with the threshold trait. line-threshold model [15] for:

[0065] where β 1(2) is the fixed effect vector; g 1(2) is the SNP effect vector; e 1(2) is the random residual vector; X 1(2) for β 1(2) The correlation matrix of ; Z is the genotype indicator matrix (the assignments 0, 1, and 2 correspond to 11, 12, and 22 of the genotype, respectively). Let v'=[y' 1 , l′], given β and g, v obeys the following distribution:

[0066] v | β , g , R ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a bayes method for joint estimation genomic of continuous traits and threshold traits based on genomic estimated breeding value. The bayes method is a new bayes method based on a line-threshold model, called as LT-BayesC pi used for joint estimation of continuous traits and threshold traits. Simulation data and the fourteenth QTL-MAS international symposium public data are used for verifying LT-VayesC pi. Accuracy of genomic prediction and BayesC pi and Bayes TCpi based on a single character model are compared. Factors influencing performance representations are also researched. The result of the bayes method shows that genomic prediction of threshold traits with LT-BayesCpi is more accurate than that with BayesTCpi. However, accuracy of continuous traits is the same as that of BayesCpi.

Description

technical field [0001] The invention relates to a Bayesian method for jointly estimating the genome breeding value of continuous traits and threshold traits. Background technique [0002] With the development of single nucleotide polymorphism (SNP) chips and genotype sequencing technologies, many genome-wide polymorphisms have been used in animal and plant breeding practices. Genome selection can use the whole genome marker information to predict the genetic value of breeding stock without the phenotype information of the individual itself. In the classical genome prediction process, the SNP effects are first estimated using individual composition parameters with both genotype and phenotype information, and then these estimated effects are used to construct prediction equations to calculate their genomic breeding values ​​based on the genotypes of candidate individuals (GEBVs). Therefore, in genomic selection, a suitable model is the key to accurately predict genomic breed...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/24
CPCG16B40/00
Inventor 王重龙丁向东李秀金钱蓉张勤
Owner INST OF ANIMAL HUSBANDRY & VETERINARY MEDICINE ANHUI ACAD OF AGRI SCI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com