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首页> 外文会议>International Conference on Intelligence Science and Big Data Engineering >A Comparative Study of Joint-SNVs Analysis Methods and Detection of Susceptibility Genes for Gastric Cancer in Korean Population
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A Comparative Study of Joint-SNVs Analysis Methods and Detection of Susceptibility Genes for Gastric Cancer in Korean Population

机译：韩国人口胃癌胃癌敏感基因的比较研究

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Many joint-SNVs (single-nucleotide variants) analysis methods were proposed to tackle the 'missing heritability' problem, which emphasizes that the joint genetic variants can explain more heritability of traits and diseases. However, there is still lack of a systematic comparison and investigation on the relative strengths and weaknesses of these methods. In this paper, we evaluated their performance on extensive simulated data generated by varying sample size, linkage disequilibrium (LD), odds ratios (OR), and minor allele frequency (MAF), which aims to cover almost all scenarios encountered in practical applications. Results indicated that a method called Statistics-space Boundary Based Test (S-space BBT) showed stronger detection power than other methods. Results on a real dataset of gastric cancer for Korean population also validate the effectiveness of the S-space BBT method.
机译：提出了许多关节SNV（单核苷酸变体）分析方法来解决“遗失性遗传性”问题，这强调联合遗传变异可以解释更多的特征和疾病的可遗传性。然而，仍然缺乏对这些方法的相对优势和弱点的系统比较和调查。在本文中，我们评估了通过不同样品大小，连杆不平衡（LD），差异比率（或）和次要等位基因频率（MAF）产生的广泛模拟数据的性能，其旨在涵盖实际应用中遇到的几乎所有情景。结果表明，一种称为统计空间基于基于基于的测试（S空间BBT）的方法显示出比其他方法更强的检测能力。结果韩国人群胃癌真实数据集还验证了S空间BBT方法的有效性。

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