基于最小二乘估计的数量性状基因座的复合区间定位法

数量性状基因座（ＱＴＬ）的复合区间定位法是区间定位法的１种改进方法，它大大提高了ＱＴＬ定位的准确性，但计算上比较复杂和费时．由于其似然比统计量的联合分布未知，故准确的显著性测验临界值必须采用排列测验法或模拟抽样法进行估计，但其复杂费时的计算使得这些经验方法显得不实用．本文给出基于最小二乘估计的复合区间定位法，它保持了复合区间定位的基本性质，但在计算上要比基于最大似然估计的方法简单和快速得多．由于它对性状的分布无需特殊的要求，因而有更广的适用范围．通过消除模型中冗余的标记，可使数值计算速度进一步提高．这样，用经验方法估计显著临界值就变得可行了．另外，消除冗余标记还可提高ＱＴＬ定位的准确性，改进ＱＴＬ效应的估值．文中最后提出了复合区间定位的实用程序

Composite Interval Mapping of Quantitative Trait Loci Based on Least Squares Estimation

An approach of composite interval mapping (CIM) of quantitative trait loci (QTLs) based on least squares estimation is described in the present paper. The method remains the basic feature of CIM, but is much simpler and quicker than the maximum likelihood based approach . It does not need special assumptions on trait distribution, so it is widely applicable. By eliminating redundant markers from the models, numerical computation can be speeded up further. That makes the use of permutation test feasible. Eliminating redundant markers can also increase the power of QTL mapping and improve the estimates of QTL effect. A practical procedure of composite interval mapping is suggested.