Simulating association studies: a data-based resampling method for candidate regions or whole genome scans.
BACKGROUND
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.
Wright
Fred A
FA
Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu
Huang
Hanwen
H
Guan
Xiaojun
X
Gamiel
Kevin
K
Jeffries
Clark
C
Barry
William T
WT
de Villena
Fernando Pardo-Manuel
FP
Sullivan
Patrick F
PF
Wilhelmsen
Kirk C
KC
Zou
Fei
F
D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D004252:DNA Mutational Analysis / Q000379:methods*; D030541:Databases, Genetic; D014644:Genetic Variation / Q000235:genetics; D016247:Information Storage and Retrieval / Q000379:methods; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D018401:Sample Size; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012689:Sequence Homology, Nucleic Acid