This is an archive of papers published by the staff and faculty of Fox Chase Cancer Center. For questions about content, please contact Talbot Research Library
Last updated on
Klein AP , Kovac I , Sorant AJ , Baffoe-Bonnie A , Doan BQ , Ibay G , Lockwood E , Mandal D , Santhosh L , Weissbecker K , Woo J , Zambelli-Weiner A , Zhang J , Naiman DQ , Malley J , Bailey-Wilson JE
Importance sampling method of correction for multiple testing in affected sib-pair linkage analysis
BMC Genet. 2003 ;4 Suppl 1 :S73
PMID: 14975141 URL: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=14975141
AbstractUsing the Genetic Analysis Workshop 13 simulated data set, we compared the technique of importance sampling to several other methods designed to adjust p-values for multiple testing: the Bonferroni correction, the method proposed by Feingold et al., and naive Monte Carlo simulation. We performed affected sib-pair linkage analysis for each of the 100 replicates for each of five binary traits and adjusted the derived p-values using each of the correction methods. The type I error rates for each correction method and the ability of each of the methods to detect loci known to influence trait values were compared. All of the methods considered were conservative with respect to type I error, especially the Bonferroni method. The ability of these methods to detect trait loci was also low. However, this may be partially due to a limitation inherent in our binary trait definitions.
Notes1471-2156 Journal Article