Data from: CLIP test: a new fast, simple and powerful method to distinguish between linked or pleiotropic quantitative trait loci in linkage disequilibria analysis

An important question arises when mapping quantitative trait loci (QTLs) for genetically correlated traits: is the correlation due to pleiotropy (a single QTL affecting more than one trait) and/or close linkage (different QTLs that are physically close to each other and influence the traits)? In this article, we propose the Close Linkage versus Pleiotropism (CLIP) test, a fast, simple and powerful method to distinguish between these two situations. The CLIP test is based on the comparison of the square of the observed correlation between a combination of apparent effects at the marker level to the minimal value it can take under the pleiotropic assumption. A simulation study was performed to estimate the power and alpha risk of the CLIP test and compare it to a test that evaluated whether the confidence intervals of the two QTLs overlapped or not (CI test). On average, the CLIP test showed a higher power (68%) to detect close-linked QTLs than the CI test (43%) and a same alpha risk (4%).在针对遗传相关性状开展数量性状位点（quantitative trait loci, QTL）定位研究时，一个关键科学问题应运而生：性状间的相关性究竟源于多效性（pleiotropy，即单个QTL调控多个性状），还是紧密连锁（close linkage，即物理位置相邻的不同QTL分别影响对应性状）？本文提出了紧密连锁与多效性检验（Close Linkage versus Pleiotropism, 下文简称CLIP检验）——一种快速、简洁且功效强劲的方法，用以区分上述两种情形。CLIP检验的核心原理为：将标记水平上表观效应组合的观测相关系数平方，与多效性假设下该相关系数平方所能取到的最小值进行比较。本研究通过模拟实验，评估了CLIP检验的统计功效与α风险（一类错误率），并将其与「检验两个QTL置信区间是否重叠」的CI检验（CI test）进行了对比分析。平均而言，CLIP检验检测紧密连锁QTL的统计功效可达68%，高于CI检验的43%，且二者的α风险均为4%。