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Title: Analisis Data SNP (Single Nucleotide Polymorphism) Menggunakan Model Regresi Logistik
Other Titles: Single Nucleotide Polymorphism Data Analysis Using Logistic Regression Model
Authors: Mose, Anna Juliana
Keywords: SNP (Single Nucleotide Polymorphism);Genome-wide Association Studies (GWAS);Logistic regression
Issue Date: 2020
Abstract: The aims of this study is to identify which SNP (Single Nucleotide Polymorphism) is associated with certain diseases or traits. The method used is Logistic Regression Model. Based on the statistical value of Logistic Regression, obtained p-value to reject or to accept H_0 (null hypothesis), that is, the SNP is not associated with the presence of a particular disease or trait with level of significance (𝛼 = 0.05). In the decision making which H_0 is rejected or accepted also used a level of significance using Bonferroni Correction and a level of significance from R Application default. The significant SNP from the level of significance (𝛼 = 0.05), level of significance using Bonferroni Correction and the R application default respectively are 4213 SNPs, 2211 SNPs, and 334 SNPs.
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