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一种在同胞对连锁分析中调整协变量的统计方法。

A statistical method for adjusting covariates in linkage analysis with sib pairs.

作者信息

Wu Colin O, Zheng Gang, Leifer Eric, Follmann Dean, Lin Jing-Ping

机构信息

Office of Biostatistics, DECA, National Heart, Lung, and Blood Institute, 2 Rockledge Center, Bethesda, Maryland, USA.

出版信息

BMC Genet. 2003 Dec 31;4 Suppl 1(Suppl 1):S51. doi: 10.1186/1471-2156-4-S1-S51.

Abstract

BACKGROUND

We propose a statistical method that includes the use of longitudinal regression models and estimation procedures for adjusting for covariate effects in applying the Haseman-Elston (HE) method for linkage analysis. Our methodology, which uses the covariate adjusted trait, contains three steps: a) modelling the covariate-adjusted population means of quantitative traits through regression; b) estimating the value of covariate-adjusted quantitative traits; and c) evaluating the linkage between the adjusted trait values and the markers based on alleles shared identically by descent.

RESULTS

We applied our adjusted HE method and the standard HE method in S.A.G.E. to the sib-pair subset of the Framingham Heart Study distributed by Genetic Analysis Workshop 13 with systolic blood pressure as the quantitative trait. Both methods gave similar patterns for the LOD scores, and exhibited highest multipoint LOD scores near location 70 cM of chromosome 12.

CONCLUSION

The adjusted HE method has two major advantages over the standard HE method used in S.A.G.E.: a) it has the capability to handle longitudinal data; b) it provides a more natural approach for adjusting the repeatedly measured covariates from each subject.

摘要

背景

我们提出一种统计方法,该方法在应用哈斯曼 - 埃尔斯顿(HE)方法进行连锁分析时,包括使用纵向回归模型和估计程序来调整协变量效应。我们的方法使用经协变量调整后的性状,包含三个步骤:a)通过回归对定量性状的协变量调整后的总体均值进行建模;b)估计协变量调整后的定量性状的值;c)基于通过血缘相同共享的等位基因评估调整后的性状值与标记之间的连锁关系。

结果

我们在S.A.G.E.中,将调整后的HE方法和标准HE方法应用于遗传分析研讨会13分发的弗雷明汉心脏研究的同胞对亚组,以收缩压作为定量性状。两种方法给出的对数优势(LOD)分数模式相似,并且在12号染色体70厘摩附近表现出最高的多点LOD分数。

结论

与S.A.G.E.中使用的标准HE方法相比,调整后的HE方法有两个主要优点:a)它有能力处理纵向数据;b)它为调整每个受试者重复测量的协变量提供了一种更自然的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b728/1866488/dcb9b6385028/1471-2156-4-S1-S51-1.jpg

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