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FluRF, an automated flu virus reassortment finder based on phylogenetic trees

机译:FluRF,基于系统发生树的自动流感病毒重排查找器

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Reassortments are events in the evolution of the genome of influenza (flu). As reassortments have been implicated in major human pandemics of the last century, their identification has become a health priority. While such identification can be done on a small dataset by a biologist (using phylogenetic trees), databases of flu sequences are growing exponentially, so that it is imperative to develop automated identification methods. However, current methods are limited to pairwise segment comparisons. We present FluRF, a fully automated flu virus reassortment finder. FluRF is inspired by the visual approach to reassortment identification and thus uses the reconstructed phylogenetic trees of the individual segments and the full genome. We also present a simple flu evolution simulator, used to produce synthetic datasets to tune the FluRF parameters. On synthetic datasets produced by our flu evolution simulator, FluRF, tuned for a 0% false positive rate, yielded false negative rates of 10% or less. FluRF corroborated two new reassortments identified by visual analysis of 75 Human H3N2 New York flu strains from 2005–2008 and gave partial verification of reassortments found using another bioinformatics method. FluRF finds reassortments by a bottom-up search of the full-genome and segment-based phylogenetic trees for candidate clades-groups of one or more sampled viruses that are separated from the other variants from the same season. Candidate clades in each tree are tested to guarantee confidence values, using the lengths of key edges as well as other tree parameters; clades with reassortments must have validated incongruencies among segment trees. FluRF demonstrates robustness of prediction for geographically and temporally expanded datasets, and is not limited to finding reassortments with previously collected sequences. The complete source code is available from lcbb.epfl.ch/software.html.
机译:重新分类是流感(流感)基因组进化中的事件。由于重配已牵涉到上个世纪的主要人类大流行中,因此,对其进行识别已成为健康方面的优先事项。虽然可以由生物学家在较小的数据集上进行这种识别(使用系统树),但流感序列的数据库呈指数增长,因此必须开发自动化的识别方法。但是,当前的方法仅限于成对段比较。我们展示了FluRF,这是一种全自动的流感病毒重排查找程序。 FluRF受到可视化方法的重新分配识别的启发,因此使用了各个片段和整个基因组的重建系统树。我们还提供了一个简单的流感进化模拟器,用于生成合成数据集以调整FluRF参数。在由我们的流感进化模拟器FluRF生成的合成数据集上,将假阳性率调整为0%,产生的假阴性率则为10%或更低。 FluRF证实了通过视觉分析从2005年至2008年对75例人类H3N2纽约流感菌株进行鉴定而确定的两个新重排,并使用另一种生物信息学方法对发现的重排进行了部分验证。 FluRF通过从下至上搜索全基因组和基于片段的系统发育树,找到一种或多种与同一季节的其他变种分离的一种或多种采样病毒的候选进化枝群,从而找到重组。使用关键边缘的长度以及其他树参数对每棵树中的候选进化枝进行测试,以确保置信度值;重新分类的进化枝必须在片段树之间验证不一致性。 FluRF证明了对地理和时间上扩展的数据集进行预测的鲁棒性,并且不仅限于查找与先前收集的序列有关的重排。完整的源代码可从lcbb.epfl.ch/software.html获得。

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