Summary: | 研究指出,在不同人類個體的DNA序列中,只有0.1%的基因組排列是相異的,而其餘的序列則是相同的。這些相異的基因組排列則被稱為單一核苷酸(SNP)。Affymetrix公司發展出一種DNA晶片技術稱之為Affymetrix GeneChip Mapping 100K SNP set,此晶片可用來決定單一核苷酸資料的基因類型(genotype)。Affymetrix公司採用預設「動態模型演算法」(DM)來決定基因型態。本論文的研究目的是探討與示範對於DM方法中預設的S值的四種修正方式。而這四種修正的方法分別是: (1) Standardized L value,(2) Median-polished L value,(3) Median-center L value,和(4) Median-standardized L value。為了比較S值與四種改進方法,本研究藉由SNP的模擬資料來進行比較。資料的模擬是基於利用改寫過的階層式之Bolstad模型(2004),而模擬模型的參數估計是利用華人細胞株及基因資料庫中95位台灣人的100K SNP資料。根據AA模型與AB模型模擬資料的基因型態正確率,Standardized L value是最好的判斷基因型態之方法。在另一方面,因為DM方法並不是設計來決定Null模型的基因型態,因此對於Null模型模擬資料的基因型態判斷會有問題。關於Null模型的基因型態判斷,本論文提供了一些簡短的討論與建議。然而,依然需要進一步的研究探討。
=== It is known there is only 0.1% in the DNA sequences that is different among human beings, and the rest of them are the same. These differences in DNA sequences are defined as SNPs (Single Nucleotide Polymorphism). The Affymetrix, Inc. had developed a DNA chip technology called Affymetrix GeneChip Mapping 100K SNP set for SNP data used to determine the genotype call. The default algorithm applied by Affymetrix, Inc. to decide genotype calls is the Dynamic Model-based (DM) algorithm. This study aimed to investigate and demonstrate four different ways to modify the basic component used in DM algorithm, namely, the S value. These four modified methods include: (1) Standardized L value, (2) Median-polished L value, (3) Median-centered L value, and (4) Median-standardized L value. In order to compare the S value with the four modified L values, a simulation study was conducted. A hierarchical version of Bolstad’s model (2004) was adopted to simulate the SNP Data. The parameters for the simulation model were estimated based on 95 Taiwanese 100K SNPs data from Taiwan Han Chinese Cell and Genome bank. The Standardized L value was proven to be the best method based on the accuracy of the genotype calls determined according to the simulated data of AA model and AB model. On the other hand, the genotype call for simulated data under Null model is problematic since the DM approach is not designed to determine the Null model. We have given some brief discussion and remarks of the genotype call for Null model. However, further research is still needed.
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