Please use this identifier to cite or link to this item:
https://doi.org/10.1002/sim.4391
DC Field | Value | |
---|---|---|
dc.title | Estimating the number of true discoveries in genome-wide association studies | |
dc.contributor.author | Lee, W. | |
dc.contributor.author | Gusnanto, A. | |
dc.contributor.author | Salim, A. | |
dc.contributor.author | Magnusson, P. | |
dc.contributor.author | Sim, X. | |
dc.contributor.author | Tai, E.S. | |
dc.contributor.author | Pawitan, Y. | |
dc.date.accessioned | 2014-11-26T05:02:55Z | |
dc.date.available | 2014-11-26T05:02:55Z | |
dc.date.issued | 2012-05 | |
dc.identifier.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 | |
dc.identifier.issn | 02776715 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/108918 | |
dc.description.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. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/sim.4391 | |
dc.source | Scopus | |
dc.subject | Complex diseases | |
dc.subject | False discovery rate | |
dc.subject | High-throughput data | |
dc.subject | Statistical genetics | |
dc.type | Article | |
dc.contributor.department | LIFE SCIENCES INSTITUTE | |
dc.contributor.department | SAW SWEE HOCK SCHOOL OF PUBLIC HEALTH | |
dc.description.doi | 10.1002/sim.4391 | |
dc.description.sourcetitle | Statistics in Medicine | |
dc.description.volume | 31 | |
dc.description.issue | 11-12 | |
dc.description.page | 1177-1189 | |
dc.description.coden | SMEDD | |
dc.identifier.isiut | 000304088900016 | |
Appears in Collections: | Staff Publications |
Show simple item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.