LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present.
LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present.
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LRTAE：存在表型和/或基因型错误分类错误时，遗传关联与病例/控制数据的统计能力提高。
DOI：
10.1186/1471-2156-7-24
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发表时间：
2006-04-27
期刊：
影响因子：
2.9
通讯作者：
Gordon, Derek
中科院分区：
文献类型：
--
作者：
Barral, Sandra;Haynes, Chad;Stone, Millicent;Gordon, Derek
在统计遗传学领域，表型和基因型错误分类错误可以大大降低检测与遗传病例/对照研究相关性的能力。错误分类也可以使群体频率参数如基因型、单体型或多位点基因型频率产生偏差。这些问题在病例/对照设计中特别令人关注，因为缺少重复采样，无法检测误分类错误。我们开发了一个双抽样程序的情况下/控制的遗传关联使用似然比检验框架。已经提出了不同的方法来处理误分类错误。我们之所以选择似然框架，是因为误分类概率可以很容易地纳入统计框架和假设检验。该统计量被称为允许误差的似然比检验（LRTae），可通过软件下载免费获得。我们将我们的程序应用于模拟病例/对照数据的10，000次重复，其中我们引入了表型错误分类错误。所考虑的表型是强直性脊柱炎（AS）。对于所考虑的显著性水平（5%、1%、0.1%、0.01%），LRTae方法把握度始终大于LRTstd把握度。LRTae方法相对于LRTstd方法的功效增益随着显著性水平变得更加严格而增加。多位点基因型频率估计LRTTae方法比估计LRTstd方法更准确。LRTae方法可应用于病例/对照框架中的单位点基因型、多位点基因型或多位点单倍型，并且当存在基因型和/或表型错误时，可以更有效地检测病例/对照研究中的关联。此外，LRTae方法提供了病例和对照基因型频率的渐近无偏估计，以及表型和/或基因型错误分类率的估计。
In the field of statistical genetics, phenotype and genotype misclassification errors can substantially reduce power to detect association with genetic case/control studies. Misclassification also can bias population frequency parameters such as genotype, haplotype, or multi-locus genotype frequencies. These problems are of particular concern in case/control designs because, short of repeated sampling, there is no way to detect misclassification errors. We developed a double-sampling procedure for case/control genetic association using a likelihood ratio test framework. Different approaches have been proposed to deal with misclassification errors. We have chosen the likelihood framework because of the ease with which misclassification probabilities may be incorporated into in the statistical framework and hypothesis testing. The statistic is called the Likelihood Ratio Test allowing for errors (LRTae) and is freely available via software download. We applied our procedure to 10,000 replicates of simulated case/control data in which we introduced phenotype misclassification errors. The phenotype considered is Ankylosing Spondylitis (AS). The LRTae method power was always greater than LRTstd power for the significance levels considered (5%, 1%, 0.1%, 0.01%). Power gains for the LRTae method over the LRTstd method increased as the significance level became more stringent. Multi-locus genotype frequency estimates using LRTae method were more accurate than estimates using LRTstd method. The LRTae method can be applied to single-locus genotypes, multi-locus genotypes, or multi-locus haplotypes in a case/control framework and can be more powerful to detect association in case/control studies when both genotype and/or phenotype errors are present. Furthermore, the LRTae method provides asymptotically unbiased estimates of case and control genotype frequencies, as well as estimates of phenotype and/or genotype misclassification rates.
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影响因子：
30.8
作者：
Clayton, DG;Walker, NM;Todd, JA
通讯作者：
Todd, JA
影响因子：
9.8
作者：
Wang, K;Sheffield, VC
通讯作者：
Sheffield, VC
影响因子：
1.9
作者：
BROSS, I
通讯作者：
BROSS, I
影响因子：
2.7
作者：
MOTE, VL;ANDERSON, RL
通讯作者：
ANDERSON, RL
影响因子：
--
作者：
ROBINSON, WP;VANDERLINDEN, SM;THOMSON, G
通讯作者：
THOMSON, G