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題名 | 最大概度和迴歸區間定位法在定位胚乳數量性狀基因座之比較研究=A Comparison of Maximum Likelihood and Regression Interval Mapping for Quantitative Trait Loci Controlling Endosperm Traits |
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作者 | 王敏倫; 高振宏; | 書刊名 | 作物、環境與生物資訊 |
卷期 | 7:2 2010.06[民99.06] |
頁次 | 頁73-92 |
分類號 | 373.4 |
關鍵詞 | 數量性狀基因座; 區間定位法; 最大概度; 迴歸區間定位法; 胚乳; Quantitative trait loci; Interval mapping; Maximum likelihood; Regression interval mapping; Endosperm; |
語文 | 中文(Chinese) |
中文摘要 | 摘要 最大概度 (maximum likelihood; ML)區間定位法定位數量性狀基因座 (quantitative trait loci; QTL)的策略,係利用兩個相鄰遺傳標識所形成的標識區間,系統性地檢驗區間內的每一 位置是否有QTL 存在。由於ML 區間定位法求解MLE 的方式過於複雜且耗時,因而有迴歸 (regression; REG)區間定位法的出現作為一ML 區間定位法之近似法。雖然已有研究指出ML 和REG 區間定位法在定位一般二倍體控制之數量性狀時,兩方法的差異可能很顯著,但由於 REG 區間定位法能簡化計算過程,且也有可能產生非常類似的結果,故也廣受歡迎。本文從解 析和模擬兩個層面,探討ML區間定位法與REG區間定位法在定位控制F3種子胚乳性狀的QTL 時之差別。在解析上,REG 區間定位法對ML 區間定位法的近似程度,取決於條件機率和條件 後驗機率的相似程度,探究影響這兩種條件機率相似程度的因素便可確知導致兩方法產生差異 的因素。模擬結果顯示,在大樣本數、高遺傳率、窄標識區間時,ML 與REG 定位法對QTL 的估計與定位的效果皆佳。且對於累加性作用與QTL 位置的估計差異較小;然而在較強的第 一與第二顯性作用下,REG 區間定位法的表現較ML 區間定位法的表現為差。REG 定位法的 參數估計值普遍有較大的機差均方 (mean square error; MSE),且檢定參數時其概度比檢定 (likelihood ratio test,LRT)統計量相對較小,顯示ML 區間定位法在精確度、精準度與偵測能 力皆優於REG 區間定位法;兩方法在參數與位置的估計值、估計值的MSE、對QTL 的偵測能 力、及LRT 統計量等方面的差距,會隨著樣本數減少,遺傳率降低,標識區間變寬而愈趨明顯。 特別值得關注的是,兩方法在二倍體的定位比較中,遺傳率小的情況下,兩種方法傾向有較小 差異。但在胚乳性狀定位上,遺傳率小的情況下,兩種方法也有頗大之差異。另外,ML 定位 法超越REG 定位法的優勢為其能正確估計隨機誤差的變方,而REG 定位法會高估隨機誤差變 方。REG 定位法亦無法分別估計兩種顯性作用,若要個別估計顯性作用,必須使用ML 區間定 位法。 |
英文摘要 | ABSTRACT The differences between maximum likelihood (ML) and regression (REG) interval mapping in the analysis of quantitative trait loci (QTL) controlling endosperm traits of F3 seeds were investigated analytically and numerically by simulation. Analytically, the similarity between the conditional probabilities in REG interval mapping and the conditional posterior probabilities in ML interval mapping determines the approximation of REG to ML interval mapping. Therefore, investigating the factors affecting the similarity between the two kinds of probabilities can distinguish differences between the two methods. Simulations are performed to compare the two methods in detecting QTL under different sample sizes, heritability levels, interval sizes and dominance effects. The results show that the approximation of REG to ML interval mapping might not be good for QTL with large first and second dominance effects. The REG method tended to give estimates with larger mean square error (MSE) and smaller likelihood-ratio test (LRT) statistics. It implies that the ML method tended to be more accurate, precise, and powerful as compared to the REG method, especially, with smaller sample size, lower heritability level and wider marker interval. Another advantage of the ML method over the REG method is that it provided a better estimate of the residual variance. The REG method tended to overestimate the residual variance. Furthermore, the REG method had the problem to estimate the two dominance effects, and the ML method had the ability to estimate these two dominance effects separately. |
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