A Bayesian approach to detect QTL affecting a simulated binary and quantitative trait
2011

Detecting Genetic Traits Using Bayesian Methods

Sample size: 2326 publication Evidence: moderate

Author Information

Author(s): Aniek C. Bouwman, Luc L.G. Janss, Henri C.M. Heuven

Primary Institution: Wageningen University

Hypothesis

The quantitative and binary traits in the dataset are affected by the same QTL.

Conclusion

The Bayesian variable selection method was successful for genome-wide association studies and was reasonably fast with dense marker maps.

Supporting Evidence

  • The Bayesian method successfully mapped 8 out of 30 additive QTL for the quantitative trait.
  • For the binary trait, 11 out of 22 additive QTL were successfully mapped.
  • The method was able to detect both epistatic pairs of QTL.

Takeaway

Scientists used a special math method to find genes that affect traits in animals, and they found many important genes quickly.

Methodology

Simulated data was analyzed using a Bayesian approach with the program iBay, focusing on both quantitative and binary traits.

Limitations

The multivariate version of iBay is still in progress, which may limit the analysis of pleiotropic QTL.

Participant Demographics

The study involved 2,326 individuals from 5 generations.

Digital Object Identifier (DOI)

10.1186/1753-6561-5-S3-S4

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