TY - JOUR
T1 - Further evidence for the increased power of LOD scores compared with nonparametric methods
AU - Durner, Martina
AU - Vieland, Veronica J.
AU - Greenberg, David A.
N1 - Funding Information:
This work was supported in part by National Institutes of Health grants NS2741, DK31775, MH48858, and DK52464 (all to D.A.G.) and by National Institute of Mental Health grants ROI-52841 and KO2-01432 (both to V.J.V.).
PY - 1999
Y1 - 1999
N2 - In genetic analysis of diseases in which the underlying model is unknown, 'model free' methods - such as affected sib pair (ASP) tests - are often preferred over LOD-score methods, although LOD-score methods under the correct or even approximately correct model are more powerful than ASP tests. However, there might be circumstances in which nonparametric methods will outperform LOD-score methods. Recently, Dizier et al. reported that, in some complex two-locus (2L) models, LOD-score methods with segregation analysis- derived parameters had less power to detect linkage than ASP tests. We investigated whether these particular models, in fact, represent a situation that ASP tests are more powerful than LOD scores. We simulated data according to the parameters specified by Dizier et al. and analyzed the data by using a (a) single locus (SL) LOD-score analysis performed twice, under a simple dominant and a recessive mode of inheritance (MOI), (b) ASP methods, and (c) nonparametric linkage (NPL) analysis. We show that SL analysis performed twice and corrected for the type I-error increase due to multiple testing yields almost as much linkage information as does an analysis under the correct 2L model and is more powerful than either the ASP method or the NPL method. We demonstrate that, even for complex genetic models, the most important condition for linkage analysis is that the assumed MOI at the disease locus being tested is approximately correct, not that the inheritance of the disease per se is correctly specified. In the analysis by Dizier et al., segregation analysis led to estimates of dominance parameters that were grossly misspecified for the locus tested in those models in which ASP tests appeared to be more powerful than LOD-score analyses.
AB - In genetic analysis of diseases in which the underlying model is unknown, 'model free' methods - such as affected sib pair (ASP) tests - are often preferred over LOD-score methods, although LOD-score methods under the correct or even approximately correct model are more powerful than ASP tests. However, there might be circumstances in which nonparametric methods will outperform LOD-score methods. Recently, Dizier et al. reported that, in some complex two-locus (2L) models, LOD-score methods with segregation analysis- derived parameters had less power to detect linkage than ASP tests. We investigated whether these particular models, in fact, represent a situation that ASP tests are more powerful than LOD scores. We simulated data according to the parameters specified by Dizier et al. and analyzed the data by using a (a) single locus (SL) LOD-score analysis performed twice, under a simple dominant and a recessive mode of inheritance (MOI), (b) ASP methods, and (c) nonparametric linkage (NPL) analysis. We show that SL analysis performed twice and corrected for the type I-error increase due to multiple testing yields almost as much linkage information as does an analysis under the correct 2L model and is more powerful than either the ASP method or the NPL method. We demonstrate that, even for complex genetic models, the most important condition for linkage analysis is that the assumed MOI at the disease locus being tested is approximately correct, not that the inheritance of the disease per se is correctly specified. In the analysis by Dizier et al., segregation analysis led to estimates of dominance parameters that were grossly misspecified for the locus tested in those models in which ASP tests appeared to be more powerful than LOD-score analyses.
UR - http://www.scopus.com/inward/record.url?scp=0343399663&partnerID=8YFLogxK
U2 - 10.1086/302181
DO - 10.1086/302181
M3 - Article
AN - SCOPUS:0343399663
SN - 0002-9297
VL - 64
SP - 281
EP - 289
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
IS - 1
ER -