Multivariate multipoint linkage analysis of quantitative trait loci
Multivariate multipoint linkage analysis of quantitative trait loci
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DOI：
10.1007/bf02359757
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发表时间：
1996-09-01
影响因子：
2.6
通讯作者：
Maes, H
中科院分区：
文献类型：
--
作者：
Eaves, LJ;Neale, MC;Maes, H
解决复杂疾病的遗传成分可能需要同时分析单个数量性状基因座(QTL)对多个变量的贡献。用似然方法来说明如何用多点连锁分析来解决多变量数据的复杂性。同胞配对数据是从一个模型中模拟出来的，在该模型中，两个QTL和特定性状的多基因效应解释了五个变量内和之间的所有同胞相似之处。多点连锁分析用于获得因遗传而具有零个、一个或两个等位基因相同的个体对概率，并将这些概率应用于加权最大似然拟合函数中。结果与传统的线性结构方程模型的结果进行了比较，以估计潜在遗传因素对多个测量中的遗传协方差的贡献。这两项分析都是使用MR程序包进行的。通过遗传协方差矩阵的前两个因子的VARIMAX旋转以纯统计学术语定义的遗传因子与通过将模型与表型和多点连锁数据进行联合拟合而获得的结构之间的一致性相对较差。
Resolution of the genetic components of complex disorders may require simultaneous analysis of the contribution of individual quantitative trait loci (QTLs) to multiple variables. A likelihood approach is used to illustrate how the complexities of multivariate data may be resolved with multipoint linkage analysis. Sibling pair data were simulated from a model in which two QTLs and trait-specific polygenic effects explained all the sibling resemblance within and between five variables. Multipoint linkage analysis was used to obtain individual pair probabilities of having zero, one, or two alleles identical by descent, and these probabilities were applied in a weighted maximum-likelihood fit function. The results were compared with those obtained using conventional linear structural equation modeling to estimate the contribution of latent genetic factors to the genetic covariance in the multiple measures. Both analyses were conducted using the Mr package. Relatively poor agreement was found between genetic factors defined in purely statistical terms by varimax rotation of the first two factors of the genetic covariance matrix and the structure obtained by fitting a model jointly to the phenotypic and the multipoint linkage data.