Estimation of significance thresholds for genomewide association scans.
Estimation of significance thresholds for genomewide association scans.
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DOI：
10.1002/gepi.20297
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发表时间：
2008-04
影响因子：
2.1
通讯作者：
Gusnanto, Arief
中科院分区：
文献类型：
--
作者：
Dudbridge, Frank;Gusnanto, Arief
对于全基因组关联研究来说，什么意义的门槛是合适的，这个问题在某种程度上还没有解决。之前的理论建议尚未在实践中得到验证，而置换测试并不能解决实验的全基因组多样性与实际测试的标记子集之间的差异。我们使用了来自Wellcome Trust病例对照联盟的基因类型来估计英国高加索人口的全基因组显着性阈值。我们在增加密度的情况下对基因型进行二次抽样，使用排列来估计名义P值，其家系误差为5%。通过外推到无限密度，我们估计全基因组的显著阈值约为7.2×10−8。为了减少计算时间，我们考虑了有效测试次数的Patterson特征值估计，但发现它太低了一个数量级，不能进行多重性校正。然而，通过将Beta分布拟合到来自排列重复的最小P值，我们证明了有效数是一个有用的启发式方法，并表明在这种情况下它的估计是一个开放的问题。我们的结论是，仍然需要排列来获得全基因组的显著阈值，但通过二次抽样、外推和估计有效测试次数，可以对同一群体的所有研究标准化阈值。
The question of what significance threshold is appropriate for genomewide association studies is somewhat unresolved. Previous theoretical suggestions have yet to be validated in practice, whereas permutation testing does not resolve a discrepancy between the genomewide multiplicity of the experiment and the subset of markers actually tested. We used genotypes from the Wellcome Trust Case-Control Consortium to estimate a genomewide significance threshold for the UK Caucasian population. We subsampled the genotypes at increasing densities, using permutation to estimate the nominal P-value for 5% family-wise error. By extrapolating to infinite density, we estimated the genomewide significance threshold to be about 7.2 × 10−8. To reduce the computation time, we considered Patterson's eigenvalue estimator of the effective number of tests, but found it to be an order of magnitude too low for multiplicity correction. However, by fitting a Beta distribution to the minimum P-value from permutation replicates, we showed that the effective number is a useful heuristic and suggest that its estimation in this context is an open problem. We conclude that permutation is still needed to obtain genomewide significance thresholds, but with subsampling, extrapolation and estimation of an effective number of tests, the threshold can be standardized for all studies of the same population.
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影响因子：
30.8
作者：
Marchini, Jonathan;Howie, Bryan;Donnelly, Peter
通讯作者：
Donnelly, Peter
影响因子：
9.8
作者：
Dudbridge, F;Koeleman, BPC
通讯作者：
Koeleman, BPC
影响因子：
3.7
作者：
SIDAK, Z
通讯作者：
SIDAK, Z
影响因子：
15.8
作者：
Ioannidis, JPA
通讯作者：
Ioannidis, JPA
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y