期刊
HEREDITY
卷 106, 期 5, 页码 825-831出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/hdy.2010.125
关键词
association mapping; genome-wide type I error rate; linkage mapping; mixed model; Monte Carlo simulation; parametric bootstrap
资金
- GABI [FKZ0315072C]
Control of the genome-wide type I error rate (GWER) is an important issue in association mapping and linkage mapping experiments. For the latter, different approaches, such as permutation procedures or Bonferroni correction, were proposed. The permutation test, however, cannot account for population structure present in most association mapping populations. This can lead to false positive associations. The Bonferroni correction is applicable, but usually on the conservative side, because correlation of tests cannot be exploited. Therefore, a new approach is proposed, which controls the genomewide error rate, while accounting for population structure. This approach is based on a simulation procedure that is equally applicable in a linkage and an association-mapping context. Using the parameter settings of three real data sets, it is shown that the procedure provides control of the GWER and the generalized genome-wide type I error rate (GWERk). Heredity (2011) 106, 825-831; doi:10.1038/hdy.2010.125; published online 20 October 2010
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