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An Adaptive Resolution Tree Visualization of Large Influenza Virus Sequence Datasets

机译:大型流感病毒序列数据集的自适应分辨率树可视化

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Rapid growth of the amount of influenza genome sequence data requires enhancing exploratory analysis tools. Results of the preliminary analysis should be represented in an easy-to-comprehend form and allow convenient manipulation of the data. We developed an adaptive approach to visualization of large sequence datasets on the web. A dataset is presented in an aggregated tree form with special representation of sub-scale details. The representation is calculated from the full phylogenetic tree and the amount of available screen space. Metadata, such as distribution over seasons or geographic locations, are aggregated/refined consistently with the tree. The user can interactively request further refinement or aggregation for different paxts of the tree. The technique is implemented in Javascript on client site. It is a part of the new AJAX-based implementation of the NCBI Influenza Virus Resource.
机译:流感基因组序列数据量的快速增长需要增强探索性分析工具。初步分析的结果应以易于理解的形式表示,并允许方便地处理数据。我们开发了一种自适应方法来可视化网络上的大序列数据集。数据集以聚集树的形式呈现,带有子尺度细节的特殊表示。该表示是根据完整的系统树和可用的屏幕空间量计算得出的。元数据(例如按季节或地理位置的分布)与树一致地聚合/优化。用户可以交互地请求针对树的不同部分的进一步细化或聚合。该技术在客户端站点上的Javascript中实现。它是NCBI流感病毒资源基于AJAX的新实施的一部分。

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