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Search algorithm for epistasis effect based on comprehensive genome-wide SNP information

机译:基于全基因组SNP信息的上位性搜索算法

摘要

PPROBLEM TO BE SOLVED: To provide a method of identifying an SNP pair having synergistic epistasis effects within an actual time, even when main effects are not confirmed with respect to a binary phenotype by using genome side SNP data. PSOLUTION: The binary phenotype data of each specimen are input and stored (1). The genotype of M pieces of single nucleotide polymorphism (SNP) with respect to each specimen are input and stored (2). Genotype-categorized counting is calculated for every phenotype with respect to each SNP (3). The genotype-categorized counting is stored by determining the validity/invalidity of analysis continuation with respect to each SNP (4). Dominant/recessive type for the phenotype is determined and stored with respect to the SNP determined to be valid for analysis continuation (5). The epistasis effects are determined and stored based on a division table based on a division table based on the phenotype and the dominant/recessive type with respect to the two SNP determined to be valid for analysis continuation, and the SNP pair to be analyzed is changed according to an analytic procedure (6). The epistasis effects are verified by logistic regression analysis with respect to the SNP pair whose epistasis effects are determined (7). PCOPYRIGHT: (C)2011,JPO&INPIT
机译:<要解决的问题:提供一种在实际时间内识别具有协同上位效应的SNP对的方法,即使在通过使用基因组侧SNP数据未确认关于二元表型的主要效应时也是如此。

解决方案:输入并存储每个样本的二进制表型数据(1)。输入并存储相对于每个样本的M个单核苷酸多态性(SNP)的基因型(2)。针对每个SNP对每种表型进行基因型分类计数(3)。通过确定针对每个SNP的分析连续性的有效性/无效性来存储按基因型分类的计数(4)。确定表型的显性/隐性类型,并相对于确定为对分析继续有效的SNP进行存储(5)。相对于被确定为对分析连续有效的两个SNP,基于基于表型和显性/隐性类型的划分表的划分表,确定并存储上位效应,并且改变待分析的SNP对。根据分析程序(6)。对于确定了上皮效应的SNP对,通过logistic回归分析验证了上皮效应(7)。

版权:(C)2011,日本特许厅&INPIT

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