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Detection of atypical genes in virus families using a one-class SVM

机译:使用一类SVM检测病毒家族中的非典型基因

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Background The diversity of viruses, the absence of universally common genes in them, and their ability to act as carriers of genetic material make assessment of evolutionary paths of viral genes very difficult. One important factor contributing to this complexity is horizontal gene transfer. Results We explore the possibility for the systematic identification of atypical genes within virus families, including viruses whose genome is not encoded by a double-stranded DNA. Our method is based on gene statistical features that differ in genes that were subject of recent horizontal gene transfer from those of the genome in which they are observed. We employ a one-class SVM approach to detect atypical genes within a virus family basing of their statistical signatures and without explicit knowledge of the source species. The simplicity of the statistical features used makes the method applicable to various viruses irrespective of their genome size or type. Conclusions On simulated data, the method can robustly identify alien genes irrespective of the coding nucleic acid found in a virus. It also compares well to results obtained in related studies for double-stranded DNA viruses. Its value in practice is confirmed by the identification of isolated examples of horizontal gene transfer events that have already been described in the literature. A Python package implementing the method and the results for the analyzed virus families are available at http://svm-agp.bioinf.mpi-inf.mpg.de webcite .
机译:背景技术病毒的多样性,其中缺乏通用基因以及它们充当遗传物质载体的能力使得评估病毒基因的进化途径非常困难。导致这种复杂性的一个重要因素是水平基因转移。结果我们探索了系统鉴定病毒家族中非典型基因的可能性,包括其基因组不是由双链DNA编码的病毒。我们的方法基于基因统计特征,这些特征的不同之处在于最近进行水平基因转移的对象与观察基因组的基因不同。我们采用一类SVM方法,根据其统计特征来检测病毒家族中的非典型基因,而无需明确了解来源物种。所使用的统计特征的简单性使得该方法可应用于各种病毒,而不管其基因组大小或类型如何。结论根据模拟数据,该方法可以可靠地鉴定外来基因,而与病毒中发现的编码核酸无关。它还与双链DNA病毒在相关研究中获得的结果进行了很好的比较。通过鉴定文献中已经描述的水平基因转移事件的分离实例,证实了其实用价值。可从http://svm-agp.bioinf.mpi-inf.mpg.de webcite获得实现该方法和所分析病毒系列结果的Python软件包。

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