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%).在对遗传相关性状进行数量性状位点（quantitative trait loci，QTLs）定位时，会出现一个关键问题：该性状间的相关性究竟源于多效性（pleiotropy，即单个QTL影响多个性状），或是紧密连锁（close linkage，即物理位置邻近且分别调控不同性状的不同QTLs），亦或是二者共同作用？本文提出了紧密连锁与多效性检验法（Close Linkage versus Pleiotropism, CLIP test），一种可快速、简便且高效区分上述两种情况的方法。CLIP检验法基于标记水平表观效应组合间观测相关系数的平方，与多效性假设下该值所能取到的最小可能值的比较。本研究通过模拟实验估算了CLIP检验法的统计效力与alpha风险（alpha risk），并将其与评估两个QTL置信区间是否重叠的检验法（置信区间检验法，CI test）进行了对比。平均而言，CLIP检验法检测紧密连锁QTLs的统计效力达68%，高于置信区间检验法的43%，且二者的alpha风险均为4%，保持一致。