BACKGROUND Inexpensive pathogen genome sequencing has had a transformative effect on the field of phylodynamics, where ever increasing volumes of data have promised real-time insight into outbreaks of infectious disease. As well as the sheer volume of pathogen isolates being sequenced, the sequencing of whole pathogen genomes, rather than select loci, has allowed phylogenetic analyses to be carried out at finer time scales, often approaching serial intervals for infections caused by rapidly evolving RNA viruses. Despite its utility, whole genome sequencing of pathogens has not been adopted universally and targeted sequencing of loci is common in some pathogen-specific fields. RESULTS In this study we highlighted the utility of sequencing whole genomes of pathogens by re-analysing a well-characterised collection of Ebola virus sequences in the form of complete viral genomes (≈19 kb long) or the rapidly evolving glycoprotein (GP, ≈2 kb long) gene. We have quantified changes in phylogenetic, temporal, and spatial inference resolution as a result of this reduction in data and compared these to theoretical expectations. CONCLUSIONS We propose a simple intuitive metric for quantifying temporal resolution, i.e. the time scale over which sequence data might be informative of various processes as a quick back-of-the-envelope calculation of statistical power available to molecular clock analyses.

中文翻译：

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单个基因与完整基因组在爆发分析中解析时间和空间的能力。

背景技术廉价的病原体基因组测序已对系统动力学领域产生了变革性的影响，其中不断增长的数据量有望实时洞悉传染病的爆发。不仅要对病原体分离物进行定量分析，对整个病原体基因组进行测序，而不是对选定的基因座进行测序，还可以在更短的时间范围内进行系统发育分析，对于迅速发展的RNA病毒引起的感染，通常接近连续的时间间隔。尽管有其用途，病原体的全基因组测序尚未得到普遍采用，并且基因座的靶向测序在某些病原体特异性领域中很普遍。结果在这项研究中，我们通过重新分析完整病毒基因组（长度约19 kb）或快速发展的糖蛋白（GP，≈2）形式的特征充分的埃博拉病毒序列集合，突出了对病原体整个基因组进行测序的实用性kb长）基因。由于数据的减少，我们已经量化了系统发育，时间和空间推断分辨率的变化，并将这些变化与理论预期进行了比较。结论我们提出了一个简单直观的度量标准来量化时间分辨率，即序列数据可能为各种过程提供信息的时间尺度，这是对分子时钟分析可用的统计能力的快速反面计算。由于数据的减少，我们已经量化了系统发育，时间和空间推断分辨率的变化，并将这些变化与理论预期进行了比较。结论我们提出了一个简单直观的度量标准来量化时间分辨率，即序列数据可能为各种过程提供信息的时间尺度，这是对分子时钟分析可用的统计能力的快速反面计算。由于数据的减少，我们已经量化了系统发育，时间和空间推断分辨率的变化，并将这些变化与理论预期进行了比较。结论我们提出了一个简单直观的度量标准来量化时间分辨率，即序列数据可能为各种过程提供信息的时间尺度，这是对分子时钟分析可用的统计能力的快速反面计算。