Lecture 9 - Mixed Effects Models - LD Score Regression

Haky Im

2022-02-09

Categories: Lecture

Learning Objectives

  • Use mixed effects model approach to correct for population structure
  • Recognize the polygenic architecture of complex traits
  • Use LD Score regression to distinguish between population structure and polygenicity driven inflation

Notes

Find the class notes here

Vignettes

References

  • Watanabe et al, “A global overview of pleiotropy and genetic architecture in complex traits” Nature Genetics 2019
  • B. Devlin and Kathryn Roeder (1999) “Genomic Control for Association Studies”, Biometrics, Vol. 55, No. 4, 997-1004.
  • H. M. Kang, J. H. Sul, S. K. Service, N. A. Zaitlen, S.-Y. Kong, N. B. Freimer, C. Sabatti, and E. Eskin, “Variance component model to account for sample structure in genome-wide association studies,” Mar. 2010.
  • A. L. Price, N. A. Zaitlen, D. Reich, and N. Patterson, “New approaches to population stratification in genome-wide association studies,” Nat Rev Genet, vol. 11, no. 7, pp. 459–463, Jun. 2010.
  • B. K. Bulik-Sullivan, P.-R. Loh, H. K. Finucane, S. Ripke, J. Yang, N. Patterson, M. J. Daly, A. L. Price, and B. M. Neale, “LD Score regression distinguishes confounding from polygenicity in genome-wide association studies,” Nat Genet, vol. 47, no. 3, pp. 291–295, Feb. 2015.

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Citation

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Haky Im (2022). Lecture 9 - Mixed Effects Models - LD Score Regression. HGEN 471 Class Notes. /post/2022/02/09/lecture-9-mixed-effects-models-ld-score-regression/

BibTeX citation

@misc{
  title = "Lecture 9 - Mixed Effects Models - LD Score Regression",
  author = "Haky Im",
  year = "2022",
  journal = "HGEN 471 Class Notes",
  note = "/post/2022/02/09/lecture-9-mixed-effects-models-ld-score-regression/"
}