Xu S
Department of Botany and Plant Sciences, University of California, Riverside 92521, USA.
Genetics. 1998 Jan;148(1):517-24. doi: 10.1093/genetics/148.1.517.
To avoid a loss in statistical power as a result of homozygous individuals being selected as parents of a mapping population, one can use multiple families of line crosses for quantitative trait genetic linkage analysis. Two strategies of combining data are investigated: the fixed-model and the random-model strategies. The fixed-model approach estimates and tests the average effect of gene substitution for each parent, while the random-model approach treats each effect of gene substitution as a random variable and directly estimates and tests the variance of gene substitution. Extensive Monte Carlo simulations verify that the two strategies perform equally well, although the random model is preferable in combining data from a large number of families. Simulations also show that there may be an optimal sampling strategy (number of families vs. number of individuals per family) in which QTL mapping reaches its maximum power and minimum estimation error. Deviation from the optimal strategy reduces the efficiency of the method.
为避免因选择纯合个体作为定位群体的亲本而导致统计功效损失，可使用多个品系杂交组合进行数量性状遗传连锁分析。研究了两种数据合并策略：固定模型和随机模型策略。固定模型方法估计并检验每个亲本基因替代的平均效应，而随机模型方法将基因替代的每种效应视为随机变量，并直接估计和检验基因替代的方差。大量的蒙特卡罗模拟验证了这两种策略表现同样出色，尽管在合并来自大量家系的数据时随机模型更可取。模拟还表明，可能存在一种最优抽样策略（家系数与每个家系个体数），在此策略下数量性状基因座定位达到最大功效和最小估计误差。偏离最优策略会降低该方法的效率。
