醫學為孕婦提供了多種產前檢測，以確保胎兒是否有染色體遺傳疾病的風 險。其中一個現在常用的技術是非侵入性產前胎兒檢測 (NIPT)。該檢測利用孕婦血液中小片段的游離 DNA 來分析，因此與其他侵入性產前檢測相比風險較低。在這項研究中，我們研究了來自全外顯子定序而不是全基因組定序的數據，來檢測胎兒是否具有拷貝數變異 (CNV) 的情形。NIPT 的主要挑戰之一是孕婦血液中的胎兒 DNA比例較低, 所以含有胎兒的資訊量較少。現在的方法和工具通常針對整個染色體或特定小範圍 DNA 的CNV。我們的目標是在不同水準的胎兒比例之下檢測三種不同大小的染色體拷貝數變異。考慮的變體大小包括小範圍 (1∼5 Mb)、大範圍 (5 Mb ∼ 一半的染色體) 和全範圍。本研究的新穎之處在於：(1) 通過資料導向的模擬找到強大的檢定統計量及其臨界值；(2) 運用統計製程管制中的西屋法則並將調整過後的西屋法則應用於統計檢定上。

Modern medicine offers a pregnant woman several prenatal screening tests to ensure whether the fetus has a risk of chromosomal conditions. One of the reliable techniques is the noninvasive prenatal testing (NIPT). This testing analyzes small fragments of DNA that circulate in a pregnant woman’s blood, so it’s low risk, relatively to other invasive prenatal tests. In this study, we investigated the data from whole exome sequencing (WES) instead of whole-genome sequencing (WGS) to detect copy number variation (CNV) of a fetal. One of the major challenges in NIPT is the low fetal fraction of DNA in the pregnant woman’s blood and therefore the low amount of information containing the fetus. The current methods and tools usually target the CNV size for whole chromosome or a specific short range of DNA. Our goal is to detect chromosome variants of three different sizes under various level of fetal fraction. The considered variants sizes include small range (1∼5 Mb), large range (5 Mb∼half chromosome), and full range. The novel parts of this research are: (1) find the powerful test statistic and their critical values through a data driven simulation; (2) apply modified Western Electric rules in statistical process control method to the test statistic.

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