摘要
本文将 Gai and Wang( 1998)的 P1、F1、P2 、B1、B2 和 F2 6个世代联合分离分析方法从 A、B、C、D4类共 17种遗传模型扩展至 E( 2对主基因 +多基因 )共 5类 2 4种遗传模型。成分分布参数估计的方法由 EM算法改进为迭代条件 EM算法 ( IECM) ,其收敛性和所获结果优于 EM算法。水稻株高例中 2对主基因 +多基因的遗传模型 ( E- 2 )优于原所获得的 1对主基因 +多基因的遗传模型 ( D)
The two major genes plus polygene Model (Model E ) of QTL in a joint analysis of P 1, F 1, P 2, B 1, B 2 and F 2 was extended to based on Gai and Wang (1998). The major steps were to establish the genetic models and respective maximum likelihood functions, to estimate the distribution parameters through iterated expectation and conditional maximization (IECM) algorithm, to select the best genetic model through AIC value and tests for goodness of fit, to estimate the genetic parameters of the best fitted model through least squares method, and to classify the individuals into major gene genotypes in terms of Bayesian posterior probability. The example of the inheritance of rice plant height which was used by Gai and Wang (1998) was further analyzed to explain the procedures. It was shown through the example that the convergence of the parameter estimation in IECM algorithm was better than that in EM algorithm, and the two major genes plus polygene model ( E 2 ) was better than the previous one major gene plus polygene model (D ).
出处
《作物学报》
CAS
CSCD
北大核心
2000年第4期385-391,共7页
Acta Agronomica Sinica
基金
国家 973项目
关键词
数量性状
混合遗传
多世代联合分析
IECM算法
Quantitative trait
Major gene plus polygene mixed inheritance
Joint analysis of multiple generations
IECM algorithmH
