Crooks Lucy, Sahana Goutam, de Koning Dirk-Jan, Lund Mogens Sandø, Carlborg Orjan
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, SE-75007 Uppsala, Sweden.
BMC Proc. 2009 Feb 23;3 Suppl 1(Suppl 1):S2. doi: 10.1186/1753-6561-3-s1-s2.
As part of the QTLMAS XII workshop, a simulated dataset was distributed and participants were invited to submit analyses of the data based on genome-wide association, fine mapping and genomic selection. We have evaluated the findings from the groups that reported fine mapping and genome-wide association (GWA) efforts to map quantitative trait loci (QTL). Generally the power to detect QTL was high and the Type 1 error was low. Estimates of QTL locations were generally very accurate. Some methods were much better than others at estimating QTL effects, and with some the accuracy depended on simulated effect size or minor allele frequency. There were also indications of bias in the effect estimates. No epistasis was simulated, but the two studies that included searches for epistasis reported several interacting loci, indicating a problem with controlling the Type I error rate in these analyses. Although this study is based on a single dataset, it indicates that there is a need to improve fine mapping and GWA methods with respect to estimation of genetic effects, appropriate choice of significance thresholds and analysis of epistasis.
作为QTLMAS XII研讨会的一部分，分发了一个模拟数据集，并邀请参与者提交基于全基因组关联、精细定位和基因组选择的数据的分析结果。我们评估了那些报告了精细定位和全基因组关联（GWA）以定位数量性状基因座（QTL）的小组的研究结果。总体而言，检测QTL的能力较高，I类错误较低。QTL位置的估计通常非常准确。在估计QTL效应方面，一些方法比其他方法要好得多，对于一些方法，准确性取决于模拟的效应大小或次要等位基因频率。效应估计中也存在偏差迹象。未模拟上位性，但两项包括上位性搜索的研究报告了几个相互作用的基因座，表明在这些分析中控制I类错误率存在问题。尽管本研究基于单个数据集，但它表明在遗传效应估计、显著性阈值的适当选择和上位性分析方面，有必要改进精细定位和GWA方法。
