Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions
Background and Purpose: Genomic selection is used to select candidates for breeding programs for organisms. In this study, we use the Bayesian model averaging (BMA) method for genomic selection by considering the skewed error distributions. Materials and Methods: In this study, we apply the BMA meth...
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Mazandaran University of Medical Sciences
2024-12-01
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| Series: | علوم بهداشتی ایران |
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| Online Access: | http://jhs.mazums.ac.ir/article-1-967-en.pdf |
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| author | Azadeh Ghazanfari Afshin Fayyaz Movaghar |
| author_facet | Azadeh Ghazanfari Afshin Fayyaz Movaghar |
| author_sort | Azadeh Ghazanfari |
| collection | DOAJ |
| description | Background and Purpose: Genomic selection is used to select candidates for breeding programs for organisms. In this study, we use the Bayesian model averaging (BMA) method for genomic selection by considering the skewed error distributions.
Materials and Methods: In this study, we apply the BMA method to linear regression models with skew-normal and skew-t distributions to determine the best subset of predictors. Occam’s window and Markov-Chain Monte Carlo model composition (MC3) were used to determine the best model and its uncertainty. The Rice SNP-seek database was used to obtain real data, which included 152 single nucleotide polymorphisms (SNPs) with 6 phenotypes.
Results: Numerical studies on simulated and real data showed that, although Occam’s window ran faster than the MC3 method, the latter method suggested better linear models for the data with both skew-normal and skew-t error distributions.
Conclusion: The MC3 method performs better than Occam’s window in identifying the linear models with greater accuracy when dealing with skewed error distributions. |
| format | Article |
| id | doaj-art-2129eeb8853043e29084fe78e555c621 |
| institution | Kabale University |
| issn | 2322-553X 2981-2240 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Mazandaran University of Medical Sciences |
| record_format | Article |
| series | علوم بهداشتی ایران |
| spelling | doaj-art-2129eeb8853043e29084fe78e555c6212025-01-25T07:11:35ZengMazandaran University of Medical Sciencesعلوم بهداشتی ایران2322-553X2981-22402024-12-01124281290Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error DistributionsAzadeh Ghazanfari0Afshin Fayyaz Movaghar1 Student Research Committee, University of Mazandaran, Babolsar, Iran. Department of Statistics, School of Mathematical Sciences, University of Mazandaran, Babolsar, Iran. Background and Purpose: Genomic selection is used to select candidates for breeding programs for organisms. In this study, we use the Bayesian model averaging (BMA) method for genomic selection by considering the skewed error distributions. Materials and Methods: In this study, we apply the BMA method to linear regression models with skew-normal and skew-t distributions to determine the best subset of predictors. Occam’s window and Markov-Chain Monte Carlo model composition (MC3) were used to determine the best model and its uncertainty. The Rice SNP-seek database was used to obtain real data, which included 152 single nucleotide polymorphisms (SNPs) with 6 phenotypes. Results: Numerical studies on simulated and real data showed that, although Occam’s window ran faster than the MC3 method, the latter method suggested better linear models for the data with both skew-normal and skew-t error distributions. Conclusion: The MC3 method performs better than Occam’s window in identifying the linear models with greater accuracy when dealing with skewed error distributions.http://jhs.mazums.ac.ir/article-1-967-en.pdfgenomic selectionsingle nucleotide polymorphism (snps)bayesian model |
| spellingShingle | Azadeh Ghazanfari Afshin Fayyaz Movaghar Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions علوم بهداشتی ایران genomic selection single nucleotide polymorphism (snps) bayesian model |
| title | Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions |
| title_full | Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions |
| title_fullStr | Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions |
| title_full_unstemmed | Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions |
| title_short | Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions |
| title_sort | using the bayesian model averaging approach for genomic selection by considering skewed error distributions |
| topic | genomic selection single nucleotide polymorphism (snps) bayesian model |
| url | http://jhs.mazums.ac.ir/article-1-967-en.pdf |
| work_keys_str_mv | AT azadehghazanfari usingthebayesianmodelaveragingapproachforgenomicselectionbyconsideringskewederrordistributions AT afshinfayyazmovaghar usingthebayesianmodelaveragingapproachforgenomicselectionbyconsideringskewederrordistributions |