隨著次世代DNA定序技術與生物演算技術的興起，造就了產前非侵入性胎兒染色體基因檢測（Noninvasive Prenatal Test，簡稱NIPT）在臨床上廣泛的應用，NIPT所引發的風險相較於早期侵入性檢測方法低，因NIPT僅透過抽取孕婦血樣，取得胎兒在孕婦血液中微量的游離DNA，以檢測胎兒是否患有染色體異常之疾病的可能。再者，因非侵入性胎兒染色體基因檢測需透過估計母親血漿中胎兒DNA片段比例（Fetal DNA Fraction）作為篩檢依據，故本研究將評估五種方法之參數估計量的表現。

我們以Jiang et al.（2012）的統計方法與Jiang et al.（2016）的測序想法作為出發點，然而在真實資料中，如果FDP（Flow Evaluator Read Depth at the Locus）讀數過小或胎兒DNA片段濃度極低時，比對到參考序列的讀數FRO（Flow Evaluator Reference allele observations）會無法顯現以致不被納入計算，導致以往的估計量有所偏差，故我們主要是利用貝氏估計量來計算胎兒DNA片段比例。最後，本研究將透過統計模擬來評估幾種胎兒 DNA 片段比例估計量的表現，並以成功大學分子醫學研究所孫孝芳教授提供的資料作為實例來說明各種估計方法的結果。

With progress in next-generation sequencing (NGS), the non-invasive prenatal test (NIPT) of fetal chromosomes has been widely used in clinical medicine. The risk of NIPT is lower than invasive detection methods because NIPT obtains an amount of cell-free DNA in maternal plasma to detect whether the fetus is chromosomal abnormalities. Furthermore, the NIPT needs to estimate fetal DNA fraction as the screening basis. We will compare the performance of parameter estimates in the five methods.

If the reads count of flow evaluator read depth at the locus (FDP) or the fetal DNA fraction is too small, the reads count of flow evaluator reference allele observations (FRO) will not be observed and calculated and leads to estimated deviations. Therefore, we used Bayesian estimation to calculate the fetal DNA fraction. Finally, we will evaluate the performance of estimate for fetal DNA fraction by statistical simulations and use the data provided by Dr. H. Sunny Sun from the Institute of Molecular Medicine at the National Cheng Kung University as an example to illustrate the results of estimation methods.

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