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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >IN SILICO PHENOTYPIC SCREENING METHOD OF MUTANTS BASED ON STATISTICAL MODELING OF GENETICALLY MIXED SAMPLES
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IN SILICO PHENOTYPIC SCREENING METHOD OF MUTANTS BASED ON STATISTICAL MODELING OF GENETICALLY MIXED SAMPLES

机译：遗传混合样本统计建模的突变体硅胶表型筛选方法

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摘要

In comprehensive functional genomics projects, systematic analysis of phenotypes is vital. However, conventional phenotypic screening is done mainly by imprecise visual observation of qualitative traits, and, therefore, in silico screening techniques for quantitative traits are required. In this report, we propose in silico phenotypic screening method that utilizes a Gaussian mixture model for the trait distribution in the offspring of a mutagenized line and the likelihood ratio test between the estimated Gaussian mixture model and the wild-type single Gaussian model. In order to evaluate the proposed method, we performed a screening experiment using real trait data of Arabidopsis. In this experiment, the proposed screening method properly distinguished the mutant line from the wild-type line. Furthermore, we conducted power analysis of the proposed method and two conventional methods under various simulated conditions of sample size and distribution of trait frequency. The result of the power analysis confirmed the effectiveness of the proposed method compared to the conventional methods.
机译：在全面的功能基因组学项目中，对表型进行系统分析至关重要。然而，常规的表型筛选主要是通过对质量性状的不精确的肉眼观察来完成的，因此，需要用于数量性状的计算机筛选技术。在本报告中，我们提出了一种计算机表型筛选方法，该方法利用高斯混合模型对诱变品系的后代进行性状分布，并利用估计的高斯混合模型与野生型单高斯模型之间的似然比检验。为了评估所提出的方法，我们使用拟南芥的真实性状数据进行了筛选实验。在该实验中，所提出的筛选方法适当地将突变株与野生株区分开。此外，我们在各种模拟的样本大小和特征频率分布条件下，对提出的方法和两种常规方法进行了功率分析。功率分析的结果证实了与传统方法相比该方法的有效性。

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