位点致病性预测软件对错义突变的预测效用评估
发布时间：2018-08-25 08:39
【摘要】：通过比较不同位点致病性预测软件的预测效果和预测特点,从而根据错义突变所在疾病的类型和使用目的选择预测效果最佳的软件,为位点致病性预测软件的合理有效使用提供依据。将孟德尔疾病和复杂疾病作为数据集分类标准,使用经实验验证的致病错义突变数据集对7种位点致病性预测软件(Mutation Taster-2,Mutation Assessor,Poly Phen2,SIFT,LRT,Condel和Logit)的实际预测效果和特点进行比较分析。结果显示被测位点致病性预测软件的预测效用和特点各不相同,同时软件对于孟德尔疾病数据集的预测效果优于复杂疾病数据集;此外Condel和Logit软件作为组合型位点致病性预测软件,在孟德尔疾病和复杂疾病错义突变数据集中的预测效果均优于单一型位点致病性预测软件,但二者的敏感度和特异性差异也较大。在位点致病性预测软件的实际使用过程中,应根据错义突变所属疾病的类型和软件的特点选择最适软件,或同时使用多个预测特点互补的软件对位点的致病性进行综合预测。
[Abstract]:By comparing the prediction effect and characteristics of the pathogenicity prediction software at different loci, the best software was selected according to the type and use of the disease in which the missense mutation occurred. To provide the basis for the rational and effective use of locus pathogenicity prediction software. Using Mendelian disease and complex disease as data set classification criteria, the actual prediction results and characteristics of seven locus pathogenicity prediction software (Mutation Taster-2,Mutation Assessor,Poly Phen2,SIFT,LRT,Condel and Logit) were compared and analyzed by using the pathogenicity mutation data set verified by experiments. The results showed that the predictive utility and characteristics of the pathogenicity prediction software were different, and the prediction effect of the software for Mendelian disease data set was better than that of the complex disease data set. In addition, Condel and Logit, as combined locus pathogenicity prediction software, are superior to single type locus in predicting pathogenicity of Mendelian disease and complex disease. But the sensitivity and specificity of the two are also different. In the practical use of locus pathogenicity prediction software, the optimal software should be selected according to the type of disease and the characteristics of the software, or multiple complementary software should be used to comprehensively predict the pathogenicity of locus.
【作者单位】： 复旦大学生命科学学院;
【基金】：国家自然科学基金面上项目(No.31272299)资助
【分类号】：R440
，
本文编号：2202351
[Abstract]:By comparing the prediction effect and characteristics of the pathogenicity prediction software at different loci, the best software was selected according to the type and use of the disease in which the missense mutation occurred. To provide the basis for the rational and effective use of locus pathogenicity prediction software. Using Mendelian disease and complex disease as data set classification criteria, the actual prediction results and characteristics of seven locus pathogenicity prediction software (Mutation Taster-2,Mutation Assessor,Poly Phen2,SIFT,LRT,Condel and Logit) were compared and analyzed by using the pathogenicity mutation data set verified by experiments. The results showed that the predictive utility and characteristics of the pathogenicity prediction software were different, and the prediction effect of the software for Mendelian disease data set was better than that of the complex disease data set. In addition, Condel and Logit, as combined locus pathogenicity prediction software, are superior to single type locus in predicting pathogenicity of Mendelian disease and complex disease. But the sensitivity and specificity of the two are also different. In the practical use of locus pathogenicity prediction software, the optimal software should be selected according to the type of disease and the characteristics of the software, or multiple complementary software should be used to comprehensively predict the pathogenicity of locus.
【作者单位】： 复旦大学生命科学学院;
【基金】：国家自然科学基金面上项目(No.31272299)资助
【分类号】：R440
，
本文编号：2202351
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