caa a22 4500 378925784 CHVBK 20180305123617.0 cr unu---uuuuu 161128e20040506xx s 000 0 eng 10.2202/1544-6115.1049 doi (NATIONALLICENCE)gruyter-10.2202/1544-6115.1049 Using Importance Sampling to Improve Simulation in Linkage Analysis [Elektronische Daten] [Lars Ängquist, Ola Hössjer] In this article we describe and discuss implementation of a weighted simulation procedure, importance sampling, in the context of nonparametric linkage analysis. The objective is to estimate genome-wide p-values, i.e. the probability that the maximal linkage score exceeds given thresholds under the null hypothesis of no linkage. In order to reduce variance of the estimate for large thresholds, we simulate linkage scores under a distribution different from the null with an artificial disease locus positioned somewhere along the genome. To compensate for the fact that we simulate under the wrong distribution, the simulated scores are reweighted using a certain likelihood ratio. If the sampling distribution are properly chosen the variance of the corresponding estimate is reduced. This results in accurate genome-wide p-value estimates for a wide range of large thresholds with a substantially smaller cost adjusted relative efficiency with respect to standard unweighted simulation. We illustrate the performance of the method for several pedigree examples, discuss implementation including the amount of variance reduction and describe some possible generalizations. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston Computation nationallicence Genetics nationallicence Nonparametric linkage analysis nationallicence importance sampling nationallicence change of probability measure nationallicence exponential tilting nationallicence marker information nationallicence variance reduction nationallicence cost adjusted relative efficiency nationallicence genome-wide significance nationallicence Ängquist Lars University of Lund, Sweden aut Hössjer Ola University of Stockholm, Sweden aut Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-05-06), 1-22 3:1<1 2004 3 sagmb https://doi.org/10.2202/1544-6115.1049 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1544-6115.1049 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ängquist Lars University of Lund, Sweden aut NATIONALLICENCE 700 1- Hössjer Ola University of Stockholm, Sweden aut NATIONALLICENCE 773 0- Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-05-06), 1-22 3:1<1 2004 3 sagmb CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter