A comparison of methods for intermediate fine mapping.
A comparison of methods for intermediate fine mapping.
复制标题
中间精细映射方法的比较。
DOI：
10.1002/gepi.20179
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发表时间：
2006
影响因子：
2.1
通讯作者：
Lin,Shili
中科院分区：
文献类型：
--
作者：
Papachristou,Charalampos;Lin,Shili
低成本、高密度遗传图谱的出现，使连锁分析研究的重点转向以高置信度在狭窄区域定位假定性状基因座的方法。这一转变导致了一种新的分析方案，它扩展了传统的两阶段协议，即初步基因组扫描，然后通过在两者之间插入一个新阶段来进行精细图谱绘制。这一新的“中等”精细作图阶段的目标是以高度可信的方式将疾病基因座分离到较窄的间隔，以便关联研究能够更集中、更有效和更具成本效益。在本文中，我们比较和对比了五种可以用来完成这一中间步骤的方法。这些方法是：Lod支持法、广义估计方程(GEE)法、置信度集推理法(CSI)和两种Bootstrap方法。我们从覆盖概率和定位精度的角度对这些方法进行了比较。对几个双轨迹模型的模拟研究结果表明，这两种Bootstrap方法产生的区间具有大致正确的覆盖率。另一方面，1-LOD支持区间和由GEE方法产生的区间倾向于显著地掩盖性状基因座，而由CSI方法获得的区域倾向于掩盖基因位置。当所有方法产生的置信度区间的观测覆盖率保持相同时，通过CSI程序获得的可信区间的观测覆盖率显示出更高的定位能力，特别是当这些基因座对性状的贡献较小并且可用于分析的数据量相对较小时。然而，在样本量非常大的情况下，LOD支持间隔成为赢家。将这些方法应用于关节炎研究活动国家资料库的数据，得到了包含所有方法的已知性状基因位置的间隔，其中CSI.Genet达到了最高的精度。《流行病学》2006。©2006 Wiley-Liss，Inc.
The arrival of highly dense genetic maps at low cost has geared the focus of linkage analysis studies toward developing methods for placing putative trait loci in narrow regions with high confidence. This shift has led to a new analytic scheme that expands the traditional two‐stage protocol of preliminary genome scan followed by fine mapping through inserting a new stage in between the two. The goal of this new “intermediate” fine mapping stage is to isolate disease loci to narrow intervals with high confidence so that association studies can be more focused, efficient, and cost‐effective. In this paper, we compared and contrasted five methods that can be used for performing this intermediate step. These methods are: the lod support approach, the generalized estimating equations (GEE) method, the confidence set inference (CSI) procedure, and two bootstrap methods. We compared these methods in terms of the coverage probability and precision of localization of the resulting intervals. Results from a simulation study considering several two‐locus models demonstrated that the two bootstrap methods yield intervals with approximately correct coverage. On the other hand, the 1‐lod support intervals, and those produced by the GEE method, tend to significantly undercover the trait locus, while the regions obtained by the CSI incline to overcover the gene position. When the observed coverage of the confidence intervals produced by all the methods was held to be the same, those obtained through the CSI procedure displayed a higher ability to localize loci, especially when these loci have a minor contribution to the trait and when the amount of data available for the analysis is relatively small. However, with very large sample sizes, lod support intervals emerged as a winner. Application of the methods to the data from the Arthritis Research Campaign National Repository led to intervals containing the position of a known trait locus for all methods, with the greatest precision achieved by the CSI.Genet. Epidemiol.2006. © 2006 Wiley‐Liss, Inc.