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A hybrid bayesian approach for genome-wide association studies on related individuals.

Publication ,  Journal Article
Yazdani, A; Dunson, DB
Published in: Bioinformatics (Oxford, England)
December 2015

Both single marker and simultaneous analysis face challenges in GWAS due to the large number of markers genotyped for a small number of subjects. This large p small n problem is particularly challenging when the trait under investigation has low heritability.In this article, we propose a two-stage approach that is a hybrid method of single and simultaneous analysis designed to improve genomic prediction of complex traits. In the first stage, we use a Bayesian independent screening method to select the most promising SNPs. In the second stage, we rely on a hierarchical model to analyze the joint impact of the selected markers. The model is designed to take into account familial dependence in the different subjects, while using local-global shrinkage priors on the marker effects.We evaluate the performance in simulation studies, and consider an application to animal breeding data. The illustrative data analysis reveals an encouraging result in terms of prediction performance and computational cost.

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Published In

Bioinformatics (Oxford, England)

DOI

EISSN

1367-4811

ISSN

1367-4803

Publication Date

December 2015

Volume

31

Issue

24

Start / End Page

3890 / 3896

Related Subject Headings

  • Polymorphism, Single Nucleotide
  • Models, Genetic
  • Genotype
  • Genomics
  • Genome-Wide Association Study
  • Cattle
  • Breeding
  • Bioinformatics
  • Bayes Theorem
  • Animals
 

Citation

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Yazdani, A., & Dunson, D. B. (2015). A hybrid bayesian approach for genome-wide association studies on related individuals. Bioinformatics (Oxford, England), 31(24), 3890–3896. https://doi.org/10.1093/bioinformatics/btv496
Yazdani, A., and D. B. Dunson. “A hybrid bayesian approach for genome-wide association studies on related individuals.Bioinformatics (Oxford, England) 31, no. 24 (December 2015): 3890–96. https://doi.org/10.1093/bioinformatics/btv496.
Yazdani A, Dunson DB. A hybrid bayesian approach for genome-wide association studies on related individuals. Bioinformatics (Oxford, England). 2015 Dec;31(24):3890–6.
Yazdani, A., and D. B. Dunson. “A hybrid bayesian approach for genome-wide association studies on related individuals.Bioinformatics (Oxford, England), vol. 31, no. 24, Dec. 2015, pp. 3890–96. Epmc, doi:10.1093/bioinformatics/btv496.
Yazdani A, Dunson DB. A hybrid bayesian approach for genome-wide association studies on related individuals. Bioinformatics (Oxford, England). 2015 Dec;31(24):3890–3896.

Published In

Bioinformatics (Oxford, England)

DOI

EISSN

1367-4811

ISSN

1367-4803

Publication Date

December 2015

Volume

31

Issue

24

Start / End Page

3890 / 3896

Related Subject Headings

  • Polymorphism, Single Nucleotide
  • Models, Genetic
  • Genotype
  • Genomics
  • Genome-Wide Association Study
  • Cattle
  • Breeding
  • Bioinformatics
  • Bayes Theorem
  • Animals