Linkage disequilibrium (LD) of genetic loci is routinely estimated and graphically illustrated in genetic association studies. It has been suggested that the information in LD is also useful for association mapping and genetic association can be detected by comparing LD patterns between cases and co
A sliding-window weighted linkage disequilibrium test
✍ Scribed by Hsin-Chou Yang; Chin-Yu Lin; Cathy S.J. Fann
- Book ID
- 102222559
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 333 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0741-0395
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✦ Synopsis
Abstract
Multilocus linkage disequilibrium (LD) tests that consider inter‐marker (LD) are more powerful than single‐locus tests when disease etiology is contributed simultaneously by several linked and correlated loci. However, inclusion of redundant non‐informative markers may result in reduced testing power and/or inflated false‐positive rate, therefore selection of proper marker sets is important in such tests. We introduce a unified LD test based on a convenient marker‐selection procedure (sliding window) combined with an adjustment approach (marker weighting) to dilute the impact of nuisance markers on tests. The proposed procedure includes several conventional p‐value combination methods as its special cases. Simulation studies were performed to evaluate the impact of inclusion of nuisance markers and performance of the procedure. The results showed that testing power was often inversely proportional to the quantity of nuisance markers. Among a class of p‐value combination methods, the product p‐value method had the highest testing power. P‐value truncation somewhat reduced the testing power but controlled the false‐positive rate well. Compared with conventional unweighted approaches, the weighted strategy alleviated the false‐positive rate and/or increased testing power when nuisance markers were included. Analyses of two authentic data sets for psoriasis and Alzheimer's disease using our proposed method confirmed previous findings. Genet. Epidemiol. 2006. © 2006 Wiley‐Liss, Inc.
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