本文選題：數(shù)量性狀　切入點：質(zhì)量性狀　出處：《南方醫(yī)科大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：背景： 遺傳印記是子代某些特定的等位基因,由于來自性別不同的親本而導(dǎo)致其表現(xiàn)型出現(xiàn)差異的一種遺傳現(xiàn)象,它在復(fù)雜疾病的研究中扮演重要角色。對于人類的一個二等位基因標(biāo)記位點,當(dāng)核心家庭中個體的基因型無缺失時,Q-PAT(c)(parental-asymmetry test with any constant c for quantitative trait,數(shù)量性狀的親代不對稱檢驗,c為任意常數(shù)),是一種簡單高效的數(shù)量性狀遺傳印記效應(yīng)檢驗方法。當(dāng)核心家庭數(shù)據(jù)只有單親的信息時,Q-1-PAT(c)可用于印記效應(yīng)的檢驗。對于只有單親信息的家庭數(shù)據(jù)以及雙親信息都有的家庭數(shù)據(jù)的混合數(shù)據(jù)類型,Q-C-PAT(c)可用于合并這兩類數(shù)據(jù)并計算整體的統(tǒng)計量對遺傳印記效應(yīng)進行檢驗。然而,雖然Q-C-PAT(c)是簡單而高效的遺傳印記效應(yīng)檢驗方法,但其僅僅適用于只有兩代人的核心家庭而不適用于廣義家系數(shù)據(jù),因而浪費了大量有用的信息,最終降低其檢驗效能。另一方面,PPAT (pedigree parental-asymmetry test,基于家系數(shù)據(jù)的親代不對稱檢驗)和MCPPAT (Monte Carlo pedigree parental-asymmetry test,基于家系數(shù)據(jù)的蒙特卡羅親代不對稱檢驗)方法可用于家系數(shù)據(jù)的遺傳印記檢驗。但是,這兩種檢驗方法只能用于質(zhì)量性狀位點的遺傳印記檢驗,不適用于數(shù)量性狀位點的遺傳印記檢驗。 近年來,關(guān)聯(lián)分析已經(jīng)被廣泛應(yīng)用于質(zhì)量性狀疾病致病位點的定位研究。越來越多的研究表明,如果遺傳印記效應(yīng)存在,合并遺傳印記效應(yīng)的信息之后,關(guān)聯(lián)分析的檢驗效能會得到提升。對于二等位基因標(biāo)記位點,基于家系數(shù)據(jù)的PDT (pedigree disequilibrium test,家系不平衡檢驗)和其擴展的可處理缺失數(shù)據(jù)的MCPDT (Monte Carlo pedigree disequilibrium test,蒙特卡羅家系不平衡檢驗)方法是高效的關(guān)聯(lián)分析方法。然而,它們在進行關(guān)聯(lián)分析時,并不考慮遺傳印記效應(yīng)的影響。當(dāng)遺傳印記效應(yīng)存在時,這種做法會降低其檢驗效能。另一方面,合并遺傳印記效應(yīng)的傳遞不平衡檢驗TDT*雖然可以將遺傳印記效應(yīng)合并到關(guān)聯(lián)分析中,但是它只適用于兩代人的核心家庭,并不適用于廣義家系數(shù)據(jù)。 方法： (1)對于無基因型缺失的家系數(shù)據(jù),我們提出了Q-PPAT(c)(pedigree parental-asymmetry test with any constant c for quantitative trait,帶有任意常數(shù)c的數(shù)量性狀家系親代不對稱檢驗)以檢驗數(shù)量性狀位點的遺傳印記效應(yīng)。Q-PPAT(c)利用每個家系中所有的兩代人核心家庭數(shù)據(jù)來計算統(tǒng)計量。當(dāng)家系數(shù)據(jù)的基因型有缺失時,我們提出了Q-MCPPAT(c)(Monte Carlo pedigree parental-asymmetry test with any constant c for quantitative trait,帶有任意常數(shù)c的數(shù)量性狀蒙特卡羅家系親代不對稱檢驗)來檢驗印記效應(yīng)。該方法根據(jù)給定的或者由奠基者的基因型估計的等位基因頻率,通過使用Monte Carlo模擬與估計的方法來對大量缺失的信息進行反推。 (2)對于無基因型缺失的家系數(shù)據(jù),我們首先用PPAT方法檢驗遺傳印記效應(yīng)。然后,根據(jù)檢驗結(jié)果,從PDTp (paternal version of PDT,基于雜合子父親的PDT), PDT和PDTm (maternal version of PDT,基于雜合子母親的PDT)中選擇一個最合適的統(tǒng)計量作為關(guān)聯(lián)分析的檢驗統(tǒng)計量。然而,當(dāng)個體的基因型有缺失時,在第一階段,我們首先用MCPPAT來檢測遺傳印記效應(yīng),然后再從MCPDTp (paternal version of MCPDT,基于雜合子父親的MCPDT), MCPDT和MCPDTm (maternal version of MCPDT,基于雜合子母親的MCPDT)中選擇一個最合適的統(tǒng)計量來檢驗關(guān)聯(lián)。 結(jié)果： (1)基于不同樣本量、基因型缺失率、遺傳印記效應(yīng)和人群模型,作者進行了模擬研究以評價所提出的方法的表現(xiàn)。結(jié)果表明,在遺傳印記不存在的原假設(shè)下,Q-PPAT(c)以及Q-MCPPAT(c)皆可以較好地控制犯第Ⅰ類錯誤的概率。另一方面,檢驗效能的比較表明,Q-PPAT(c)和Q-MCPPAT(c)的檢驗效能都比只使用兩代人核心家庭數(shù)據(jù)的Q-PAT(c)要高。而且,Q-MCPPAT(c)的檢驗效能與基于完整數(shù)據(jù)的Q-PPAT(c)的檢驗效能非常接近。 (2)基于多種不同背景的模擬研究表明,當(dāng)哈代-溫伯格平衡律(Hardy-Weinberg Equilibrium, HWE)在人群中成立時,在無關(guān)聯(lián)、無遺傳印記效應(yīng)的原假設(shè)條件下,PDTI和MCPDTI的第一類錯誤率都是準(zhǔn)確的。在哈代溫-伯格平衡律在人群中不嚴(yán)格成立的模擬背景下,PDTI和MCPDTI依然可以很好地控制犯第一類錯誤的概率。當(dāng)遺傳印記效應(yīng)存在時,PDTI和MCPDTI都比PDT和TDTI*(基于家系中隨機抽取的一個核心家庭)有更加高的檢驗效能。當(dāng)遺傳印記效應(yīng)不存在時,PDTI和MCPDTI擁有與PDT幾乎同樣的檢驗效能,而且依然比TDTI*的檢驗效能高。 結(jié)論： (1)在無關(guān)聯(lián)、無遺傳印記的原假設(shè)條件下,Q-PPAT(c)和Q-MCPPAT(c)能把第一類錯誤控制得較好,這就證實了這兩種方法是有效的。另一方面,通過充分利用整個家系數(shù)據(jù),Q-PPAT(c)和Q-MCPPAT(c)與只能使用兩代人核心家庭數(shù)據(jù)的Q-C-PAT(c)方法相比,有更高的檢驗效能。Q-MCPPAT(c)利用Monte Carlo模擬和估計的方法,對大量缺失信息進行了反推,因而其檢驗效能與使用完整數(shù)據(jù)的Q-PPAT(c)方法幾乎相同。 (2)當(dāng)HWE成立時,在無遺傳印記效應(yīng)和無關(guān)聯(lián)的原假設(shè)條件下,PDTI和MCPDTI有準(zhǔn)確的第一類錯誤率,這說明PDTI和MCPDTI是有效的關(guān)聯(lián)分析方法。然而,即使HWE在人群中有輕微的偏離,PDTI和MCPDTI在原假設(shè)下,依然能較好地控制犯第一類錯誤的概率。通過合并遺傳印記效應(yīng)的信息以及充分利用廣義家系數(shù)據(jù),PDTI和MCPDTI的檢驗效能比不考慮遺傳印記效應(yīng)的PDT方法更高,而且也比只使用兩代人核心家庭的TDTI*方法要高。當(dāng)遺傳印記效應(yīng)不存在時,PDTI和MCPDTI與PDT有幾乎相同的檢驗效能,其依然比TDTI*的檢驗效能要高。總的來說,由于PDTI和MCPDTI充分利用了家系信息,而且把遺傳印記的效應(yīng)合并到關(guān)聯(lián)分析中,因而比PDT和TDTI*有更好的表現(xiàn)。
[Abstract]:Background:
Genetic imprinting is the offspring of some specific alleles from different gender parents caused a genetic phenomenon of differences in the phenotype, it plays an important role in the study of complex diseases. For human a two allele loci, when the genotype of the individual family without core the absence of Q-PAT (c) (parental-asymmetry test with any constant C for quantitative trait, the parent of asymmetric test, quantitative traits C is an arbitrary constant), is a method of testing effect of genetic mark number is simple and efficient. When the core family data only one parent information, Q-1-PAT (c) can be used to test the imprinting effect for mixed data type data information and only single parent family parents have information of family data, Q-C-PAT (c) can be used to merge these two types of data and calculate the overall statistics of genetic India Remember the effect test. However, although the Q-C-PAT (c) is a genetic imprinting effect test method is simple and efficient, but it applies only to the core family of two generations only and is not suitable for general family data, thus wasting a lot of useful information, and ultimately reduce the inspection efficiency. On the other hand, PPAT (pedigree parental-asymmetry test, based on the pedigree data of the parental asymmetry test) and MCPPAT (Monte Carlo pedigree parental-asymmetry test, based on the pedigree data of the Monte Carlo method can be used to test the asymmetry of parental genetic imprinting) test pedigree data. However, these two kinds of test methods can only be used for genetic imprinting test quality trait loci, genetic imprinting test not suitable for quantitative trait loci.
In recent years, localization of association analysis has been widely used in quality traits disease sites. More and more studies show that if there is genetic imprinting effect, after the combined effect of genetic imprinting information, inspection efficiency will be enhanced. The correlation analysis for two allele loci, pedigree data based on PDT (pedigree disequilibrium test, pedigree disequilibrium test) and its extension can deal with missing data (MCPDT Monte Carlo pedigree disequilibrium test, Monte Carlo pedigree disequilibrium test) method is an efficient analysis method. However, they are not in the correlation analysis, considering the effect of genetic imprinting effect. When the effect of genetic imprinting when this approach will reduce its effectiveness. On the other hand, with the effect of genetic imprinting transmission disequilibrium test TDT* although they can be genetic imprinting effect It is incorporated into association analysis, but it only applies to the core family of two generations and does not apply to broad family data.
Method錛，

本文編號：1559182