## Abstract The explosion of genetic information over the last decade presents an analytical challenge for genetic association studies. As the number of genetic variables examined per individual increases, both variable selection and statistical modeling tasks must be performed during analysis. Whi
A comparison of analytical methods for genetic association studies
β Scribed by Alison A. Motsinger-Reif; David M. Reif; Theresa J. Fanelli; Marylyn D. Ritchie
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 36 KB
- Volume
- 33
- Category
- Article
- ISSN
- 0741-0395
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β¦ Synopsis
on page 771, in the middle of the right hand column, the numerator on the right side of the equation should be squared and should read as follows:
EΒ½n i :
π SIMILAR VOLUMES
Population stratification is an important potential confounder of genetic case-control association studies. For replication studies, limited availability of samples may lead to imbalanced sampling from heterogeneous populations. Genomic control (GC) can be used to correct w 2 test statistics which a
## Abstract Metaβanalyses of genetic association studies are usually performed using a single polymorphism at a time, even though in many cases the individual studies report results from partially overlapping sets of polymorphisms. We present here a multipoint (or multilocus) method for multivariat
## Abstract Variable selection is growing in importance with the advent of high throughput genotyping methods requiring analysis of hundreds to thousands of single nucleotide polymorphisms (SNPs) and the increased interest in using these genetic studies to better understand common, complex diseases
## Abstract We present a range of modelling components designed to facilitate Bayesian analysis of geneticβassociationβstudy data. A key feature of our approach is the ability to combine different submodels together, almost arbitrarily, for dealing with the complexities of real data. In particular,