The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

Article, Review English OPEN
de Vlaming, Ronald; Groenen, Patrick J. F.;
(2015)

In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the u... View more
  • References (63)
    63 references, page 1 of 7

    Pharoah, P. D. P., Antoniou, A., Bobrow, M., Zimmern, R. L., Easton, D. F., Ponder, B. A. J.. Polygenic susceptibility to breast cancer and implications for prevention. Nature Genetics. 2002; 31 (1): 33-36

    Meigs, J. B., Shrader, P., Sullivan, L. M., McAteer, J. B., Fox, C. S., Dupuis, J., Manning, A. K., Florez, J. C., Wilson, P. W. F., D'Agostino, R. B., Cupples, L. A.. Genotype score in addition to common risk factors for prediction of type 2 diabetes. The New England Journal of Medicine. 2008; 359 (21): 2208-2219

    Purcell, S. M., Wray, N. R., Stone, J. L., Visscher, P. M., O'Donovan, M. C., Sullivan, P. F., Ruderfer, D. M., McQuillin, A., Morris, D. W., Oĝdushlaine, C. T., Corvin, A., Holmans, P. A., Oĝdonovan, M. C., MacGregor, S., Gurling, H., Blackwood, D. H. R., Craddock, N. J., Gill, M., Hultman, C. M., Kirov, G. K., Lichtenstein, P., Muir, W. J., Owen, M. J., Pato, C. N., Scolnick, E. M., St Clair, D., Williams, N. M., Georgieva, L., Nikolov, I., Norton, N., Williams, H., Toncheva, D., Milanova, V., Thelander, E. F., O'Dushlaine, C. T., Kenny, E., Quinn, E. M., Choudhury, K., Datta, S., Pimm, J., Thirumalai, S., Puri, V., Krasucki, R., Lawrence, J., Quested, D., Bass, N., Crombie, C., Fraser, G., Leh Kuan, S., Walker, N., McGhee, K. A., Pickard, B., Malloy, P., MacLean, A. W., Van Beck, M., Pato, M. T., Medeiros, H., Middleton, F., Carvalho, C., Morley, C., Fanous, A., Conti, D., Knowles, J. A., Paz Ferreira, C., MacEdo, A., Helena Azevedo, M., Kirby, A. N., Ferreira, M. A. R., Daly, M. J., Chambert, K., Kuruvilla, F., Gabriel, S. B., Ardlie, K., Moran, J. L., Sklar, P.. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009; 460 (7256): 748-752

    Smoller, J. W., Kendler, K., Craddock, N.. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. The Lancet. 2013; 381 (9875): 1371-1379

    Rietveld, C. A., Medland, S. E., Derringer, J.. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science. 2013; 340 (6139): 1467-1471

    Rietveld, C. A., Esko, T., Davies, G.. Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proceedings of the National Academy of Sciences of the United States of America. 2014; 111 (38): 13790-13794

    Purcell, S. M., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., De Bakker, P. I. W., Daly, M. J., Sham, P. C.. PLINK: a tool set for whole-genome association and population-based linkage analyses. The American Journal of Human Genetics. 2007; 81 (3): 559-575

    Evans, D. M., Visscher, P. M., Wray, N. R.. Harnessing the information contained within genome-wide association studies to improve individual prediction of complex disease risk. Human Molecular Genetics. 2009; 18 (18): 3525-3531

    Hoerl, A. E., Kennard, R. W.. Ridge regression: biased estimation for nonorthogonal problems. Technometrics. 1970; 12 (1): 55-67

    Malo, N., Libiger, O., Schork, N. J.. Accommodating linkage disequilibrium in genetic-association analyses via ridge regression. The American Journal of Human Genetics. 2008; 82 (2): 375-385

  • Related Research Results (1)
  • Related Organizations (4)
  • Metrics
Share - Bookmark