Assessing the Effect of Sampling Strategies on the Power of Linkage Analysis to Identify Pathway‐Specific Loci Underlying a Complex Disease

Using the simulated general population data sets, we first examined the effect of sampling strategies on the power of identifying linkage by selecting samples with (A) two affected sibs in a nuclear family and (B) one affected sib and one sib with an intermediate trait value in the upper quantiles....

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Bibliographic Details
Published in:Genetic epidemiology 2001, Vol.21 (S1), p.S754-S759
Main Authors: Guo, Xiuqing, Lin, Ying-Chao, Wang, Yaping, Cheng, Li Shu-Chuan, Yang, Huiying
Format: Article
Language:English
Subjects:
Chromosome Mapping - statistics & numerical data
Genetic Predisposition to Disease - genetics
Genetic Testing
Genetics, Population
Humans
intermediate trait
linkage
Microsatellite Repeats - genetics
Models, Genetic
pleiotropic effect
Quantitative Trait, Heritable
sampling scheme
Sampling Studies
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Summary:Using the simulated general population data sets, we first examined the effect of sampling strategies on the power of identifying linkage by selecting samples with (A) two affected sibs in a nuclear family and (B) one affected sib and one sib with an intermediate trait value in the upper quantiles. Second, we evaluated the improvement in power when analyzing correlated traits simultaneously. Under each selection criteria, 100 replicates of 300 nuclear families were sampled and analyzed with two‐point linkage analysis for ten markers (1 cM apart) from each of the candidate regions. Different genes were identified under different sampling strategies. When a gene has a pleitropic effect, it is more powerful to analyze correlated traits simultaneously, either by using a linear combination or the larger value of standardized traits, than to analyze each trait separately. © 2001 Wiley‐Liss, Inc.
ISSN:0741-0395
1098-2272
DOI:10.1002/gepi.2001.21.s1.s754