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https://doi.org/10.1002/sim.4391
Title: | Estimating the number of true discoveries in genome-wide association studies | Authors: | Lee, W. Gusnanto, A. Salim, A. Magnusson, P. Sim, X. Tai, E.S. Pawitan, Y. |
Keywords: | Complex diseases False discovery rate High-throughput data Statistical genetics |
Issue Date: | May-2012 | Citation: | Lee, W., Gusnanto, A., Salim, A., Magnusson, P., Sim, X., Tai, E.S., Pawitan, Y. (2012-05). Estimating the number of true discoveries in genome-wide association studies. Statistics in Medicine 31 (11-12) : 1177-1189. ScholarBank@NUS Repository. https://doi.org/10.1002/sim.4391 | Abstract: | Recent genome-wide association studies have reported the discoveries of genetic variants of small to moderate effects. However, most studies of complex diseases face a great challenge because the number of significant variants is less than what is required to explain the disease heritability. A new approach is needed to recognize all potential discoveries in the data. In this paper, we present a practical model-free procedure to estimate the number of true discoveries as a function of the number of top-ranking SNPs together with the confidence bounds. This approach allows a practical methodology of general utility and produces relevant statistical quantities with simple interpretation. © 2011 John Wiley & Sons, Ltd. | Source Title: | Statistics in Medicine | URI: | http://scholarbank.nus.edu.sg/handle/10635/108918 | ISSN: | 02776715 | DOI: | 10.1002/sim.4391 |
Appears in Collections: | Staff Publications |
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