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|Title:||Estimating the number of true discoveries in genome-wide association studies||Authors:||Lee, W.
False discovery rate
|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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