Title
Simulating association studies: a data-based resampling method for candidate regions or whole genome scans.
Abstract
Motivation: Reductions in genotyping costs have heightened interest in performing whole genome association scans and in the fine mapping of candidate regions. Improvements in study design and analytic techniques will require the simulation of datasets with realistic patterns of linkage disequilibrium and allele frequencies for typed SNPs. Methods: We describe a general approach to simulate genotyped datasets for standard case-control or affected child trio data, by resampling from existing phased datasets. The approach allows for considerable flexibility in disease models, potentially involving a large number of interacting loci. The method is most applicable for diseases caused by common variants that have not been under strong selection, a class specifically targeted by the International HapMap project. Results: Using the three population Phase I/II HapMap data as a testbed for our approach, we have implemented the approach in HAP-SAMPLE, a web-based simulation tool.
Year
DOI
Venue
2007
10.1093/bioinformatics/btm386
BIOINFORMATICS
Keywords
Field
DocType
allele frequency,study design,web based simulation,linkage disequilibrium
Population,Data mining,Linkage disequilibrium,International HapMap Project,Computer science,Allele frequency,Testbed,Genetic association,Single-nucleotide polymorphism,Bioinformatics,Resampling
Journal
Volume
Issue
ISSN
23
19
1367-4803
Citations 
PageRank 
References 
18
2.48
6
Authors
10
Name
Order
Citations
PageRank
Fred A. Wright112712.81
Hanwen Huang2365.63
Xiaojun Guan317730.40
Kevin Gamiel4213.06
Clark Jeffries5586.99
William T. Barry61119.97
Fernando Pardo-Manuel de Villena7498.21
patrick f sullivan816522.87
Kirk C. Wilhelmsen9243.63
Fei Zou10726.18