变异 Covid-19

人年纪大了就会不自觉地思考最后的归宿，死 Covid-19 可乎？

不停地变异是病毒的特点之一，感染数量和范围可以看作是变异的直观反应。

本文从 pango_lineage 分类学数据库出发，试图对 Covid-19 如何变异提供一个可视化视角。

代码可见我的前端程序库

The pango-lineage of Covid-19

变异 Covid-19
- Pango 数据集
- 指标可视化

Pango 数据集

本文的数据来源是 nextstrain.org 提供的数据集，它不是描述感染人数，而是从基因变异的角度描述 Covid-19 的发展动态。

auspice

数据摘要

Genomic epidemiology of SARS-CoV-2 with subsampling focused globally over the past 6 months (last updated 2022-11-13) Showing 2923 of 2923 genomes sampled between Dec 2019 and Nov 2022. A full list of sequence authors is available via the TSV files below This work is made possible by the open sharing of genetic data by research groups from all over the world. We gratefully acknowledge their contributions.

目前的病毒谱系及其在全球的分布如下图所示。

Global

图中的点代表发现的支系所在地，可以用国家对其染色。

China USA Germany

在亚洲范围内，我国的变异株也是很少的，说明我们的防疫政策隔绝了大部分疫情。

Asia

指标可视化

既然原始数据可以下载下来，我就可以对它进行定制。首先关注两个指标，它们分别是

mutational-fitness：我理解为变异适应度，代表病毒朝着某个方向稳定变异的趋势，例子是

Mutations provide the fuel for adaptation by generating genetic variation, and the effect of each mutation on fitness determines the strength and direction of selection (Charlesworth and Charlesworth 1998; Lynch et al. 1999; Eyre-Walker and Keightley 2007).

S1-mutations：我理解为变异程度，属于病毒结构性的证据，例子是

We find that spike S1 is the focus of adaptive evolution, but also identify positively-selected mutations in other genes that are sculpting the evolutionary trajectory of SARS-CoV-2.

而数据表明，Covid-19 正在从左下角向右上角进化，两个数值都有所升高