Simulating association studies: a data-based resampling method for candidate regions or whole genome scans | Zendy

Fred A. Wright | Zendy; Hanwen Huang | Zendy; Xiaojun Guan | Zendy; Kevin Gamiel | Zendy; Clark Jeffries | Zendy; William T. Barry | Zendy; Fernando PardoManuel de Villena | Zendy; Patrick F. Sullivan | Zendy; Kirk C. Wilhelmsen | Zendy; Fei Zou | Zendy

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Simulating association studies: a data-based resampling method for candidate regions or whole genome scans

Author(s) -

Fred A. Wright,

Hanwen Huang,

Xiaojun Guan,

Kevin Gamiel,

Clark Jeffries,

William T. Barry,

Fernando PardoManuel de Villena,

Patrick F. Sullivan,

Kirk C. Wilhelmsen,

Fei Zou

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm386

Subject(s) - international hapmap project , computer science , genome wide association study , linkage disequilibrium , 1000 genomes project , genetic association , selection (genetic algorithm) , data mining , resampling , population , computational biology , genome , biology , single nucleotide polymorphism , genetics , artificial intelligence , human genome , genotype , demography , sociology , gene

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.

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