Journal Mobile Options
Table of Contents
Vol. 73, No. 3, 2012
Issue release date: July 2012
Section title: Original Paper
Hum Hered 2012;73:148–158
(DOI:10.1159/000338439)

Detecting Rare Variants for Quantitative Traits Using Nuclear Families

Guo W.a, b · Shugart Y.Y.a
aDivision of Intramural Division Program, National Institute of Mental Health, National Institute of Health, Bethesda, Md., USA; bKey Laboratory for Applied Statistics of Ministry of Education and School of Mathematics and Statistics, Northeast Normal University, Changchun, China
email Corresponding Author

Yin Yao Shugart

Division of Intramural Research Program, National Institute of Mental Health National Institute of Health, Building 35, Room 3A 1000, 35 Convent Drive

Bethesda, MD 20892 (USA)

Tel. +1 301 496 4341, E-Mail kay1yao@mail.nih.gov


References

  1. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, Cho JH, Guttmacher AE, Kong A, Kruglyak L, Mardis E, Rotimi CN, Slatkin M, Valle D, Whittemore AS, Boehnke M, Clark AG, Eichler EE, Gibson G, Haines JL, Mackay TF, McCarroll SA, Visscher PM: Finding the missing heritability of complex diseases. Nature 2009;461:747–753.
  2. Schork NJ, Murray SS, Frazer KA, Topol EJ: Common vs. rare allele hypotheses for complex diseases. Curr Opin Genet Dev 2009;19:212–219.
  3. Bansal V, Libiger O, Torkamani A, Schork NJ: Statistical analysis strategies for association studies involving rare variants. Nat Rev Genet 2010;11:773–785.
  4. Li B, Leal SM: Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am J Hum Genet 2008;83:311–321.
  5. Madsen BE, Browning SR: A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet 2009;5:e1000384.
  6. Liu DJ, Leal SM: A novel adaptive method for the analysis of next-generation sequencing data to detect complex trait associating with rare variants due to gene main effects and interactions. PLoS Genet 2010;6:e1001156.

    External Resources

  7. Price AL, Kryukov GV, de Bakker PIW, Purcell SM, Staples J, Wei LJ, Sunyaev SR: Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet 2010;86:832–838.
  8. Asimit J, Zeggini E: Rare variant association analysis methods for complex traits. Annu Rev Genet 2010;44:293–308.
  9. Lin D, Tang Z: A general framework for detecting disease associations with rare variants in sequencing studies. Am J Hum Genet 2011;89:354–367.
  10. Guo W, Lin SL: Generalized linear modeling with regularization for detecting common disease rare haplotype association. Genet Epidemiol 2009;33:308–316.

    External Resources

  11. Zhou H, Sehl ME, Sinsheimer JS, Lange K: Association screening of common and rare genetic variants by penalized regression. Bioinformatics 2010;26:2375–2382.
  12. Yip WK, De G, Raby BA, Laird N: Identifying causal rare variants of disease through family-based analysis of Genetics Analysis Workshop 17 data set. BMC Proc 2011;5:S21.

    External Resources

  13. Xu X, Rakovski C, Xu X, Laird N: An efficient family-based association test using multiple markers. Genet Epidemiol 2006;30:620–626.
  14. Laird NM, Horvath S, Xu X: Implementing a unified approach to family-based tests of association. Genet Epidemiol 2000;19(suppl 1):S36–S42.
  15. Rakovski C, Xu X, Lazarus R, Laird NM: A new multimarker test for family-based association studies. Genet Epidemiol 2007;31:9–17.
  16. Zou H, Hastie T: Regularization and variable selection via the elasticnet. J R Stat Soc B 2005;67:301–320.

    External Resources

  17. Friedman J, Hastie T, Tibshirani R: Regularization paths for generalized linear models via coordinate descent. J Stat Softw 2010;33:1–22.

    External Resources

  18. Tibshirani R: Regression shrinkage and selection via the lasso. J R Stat Soc B 1996;58:267–288.
  19. Malo N, Libiger O, Schork NJ: Accommodating linkage disequilibrium in genetic-association analyses via ridge regression. Am J Hum Genet 2008;82:375–385.