多數量性狀與單數量性狀基因座於同胞對資料之 迴歸模式合併分析方法

Regression Analysis Approaches to Combine the QTL Information in Multiple Quantitative Traits Using Sib-pairs Data

李昭憲(Chao-Hsien Lee)

指導教授 ： 戴政

國立臺灣大學/公共衛生學院/流行病學研究所/博士(2004年)

https://doi.org/10.6342/NTU.2004.10003

摘要

現代遺傳學分析中的一項艱鉅任務是解決數量性狀的基因定位工作。數量性狀由於同時受到基因和環境影響，基因的作用相對地被環境作用淡化，因此要能從數量性狀外表變化分離出基因成分，除了要有特定的研究設計策略外，還需要有正確的統計分析方法。分析數量性狀的方法主要建立於對性狀解釋的模式內涵，由不同研究設計而來的不同的資料結構有不同的模式內涵。本文主要是探討在同胞對資料結構下，多數量性狀與單一數量基因座的分析方法。當單一數量基因座會同時影響到多個數量性狀在遺傳上的表現時，對這多個數量性狀進行個別基因定位，會遭遇多重檢定的問題。因此，若能合併此多個數量性狀，將其置於同一模式中分析，理論上將能提高檢定力並避免多重檢定問題。本文針對上述想法提出一個二階段式的分析方法，在第一階段中利用複迴歸分析模式與多元羅吉斯迴歸分析模式，來估計帶有遺傳連鎖訊息的迴歸參數；在模式中，皆將IBD計分數置於依變數位置，數量性狀置於自變數位置，故可考慮多種不同的數量性狀於模式中；在第二階段中，利用合併分析方法合併與連鎖有關的各迴歸係數檢定訊息，完成多數量性狀與單數量性狀基因座的連鎖工作。所提分析方法的檢定力與型一誤差之表現，以模擬方法加以討論。

關鍵字

合併分析方法 ； IBD計分數 ； 數量性狀基因座 ； 同胞對 ； 複迴歸模式 ； 多元羅吉斯迴歸模式

並列摘要

Gene mapping for quantitative trait loci (QTL) was a difficult assignment in modern genetics. It was necessary to utilize the specific genetic design and strategy and the correctly statistical method for separating the genetic factors on the variations of quantitative trait values because quantitative traits were simultaneously affected by the genetic effect and environmental effect. The methods for analyzing QTL were established by the models that were inclusive of the explanations of traits. Different methods were modeled for different data structures which were gained from different genetic design. In this study, we tried to combine the QTL information in multiple quantitative traits using sib-pairs data. We considered and concerned that if the QTL influenced more than one trait and those influenced traits were individually analyzed for detecting genetic linkage; the problems about multiple comparisons were certainly occurred and arose. To avoid the problems of multiple comparisons and to increase the power for testing genetic linkage, we developed the method which could analyze simultaneously the influenced traits for detecting genetic linkage in two stages. In the first stage, we estimated the regression coefficients contained the information of genetic linkage by utilizing multiple regression model and polytomous logistic regression model. To consider the QTL information in multiple quantitative traits, we set the estimate of IBD as the dependent variable and the influenced traits as the independent variables in these models. In the second stage, we performed the method of combining tests for the regression coefficients obtained in the first stage to detect genetic linkage. Finally, we simulated the sib-pairs data to illustrate the performances of the power and the control of type I error in our method.

並列關鍵字

QTL ； sib-pairs ； the estimate of IBD ； polytomous logistic regression model ； multiple regression model ； combining tests

參考文獻

23. John Jen Tai, Pei-Ying Shih, Shang-Ling Ou, Yih-Chang Ou, Chia-Ding Hou and Chao-Hsien Lee, (2003) A Combination Test Approach for QTL Analysis Using the Haseman-Elston Regression Model, Journal of Genetics and Molecular Biology, 14, 84-89.

1. Allison D.B.,Fernandez J.R., Heo M., and Beasley T.M.(2000) Testing the robustness of the new Haseman-Elston quantitative-trait-loci- mapping procedure. Am J Hum Genet67,249-252.

2. Alvin C. Rencher. (1998) Multivariate Statistical Inference and Applications.

3. Amos C.I., Elston R.C. (1989 a) Robust methods for the detection of genetic linkage for quantitative data form pedigrees. Genetic Epidemiology 6, 349-360.

4. Amos CI, Elston RC, Wilson A.F., and Bailey-Wilson J.E.(1989 b) A more powerful robust sib-pair test of linkage for quantitative traits. Genetic Epidemiology 6, 435-449.