ggalluvial：冲击图展示组间变化、时间序列和复杂多属性alluvial diagram

冲击图(alluvial diagram)是流程图(flow diagram)的一种，最初开发用于代表网络结构的时间变化。

实例1. neuroscience coalesced from other related disciplines to form its own field. From PLoS ONE 5(1): e8694 (2010)

实例2. Sciences封面哈扎人肠道菌群 图1中的C/D就使用了3个冲击图。详见3分和30分文章差距在哪里？

ggalluvial是一个基于ggplot2的扩展包，专门用于快速绘制冲击图(alluvial diagram)，有些人也叫它桑基图(Sankey diagram)，但两者略有区别，将来我们会介绍riverplot包绘制桑基图。

软件源代码位于Github: https://github.com/corybrunson/ggalluvial

CRNA官方演示教程: https://cran.r-project.org/web/packages/ggalluvial/vignettes/ggalluvial.html

安装

以下三种方装方式，三选1：

# 国内用户推荐清华镜像站

site="https://mirrors.tuna.tsinghua.edu.cn/CRAN"

# 安装稳定版(推荐)

install.packages("ggalluvial", repo=site)

# 安装开发版(连github不稳定有时间下载失败，多试几次可以成功)

devtools::install_github("corybrunson/ggalluvial", build_vignettes = TRUE)

# 安装新功能最优版

devtools::install_github("corybrunson/ggalluvial", ref = "optimization") 显示帮助文档

使用vignette查看演示教程

# 查看教程

vignette(topic = "ggalluvial", package = "ggalluvial")

接下来我们的演示均基于此官方演示教程，我的主要贡献是翻译与代码注释。

基于ggplot2的冲击图

原作者：Jason Cory Brunson, 更新日期：2018-02-11

1. 最简单的示例

基于泰坦尼克事件人员统计绘制性别与舱位和年龄的关系。

# 加载包

library(ggalluvial)

# 转换内部数据为数据框，宽表格模式

titanic_wide <- data.frame(Titanic)

# 显示数据格式

head(titanic_wide)

#> Class Sex Age Survived Freq

#> 1 1st Male Child No 0

#> 2 2nd Male Child No 0

#> 3 3rd Male Child No 35

#> 4 Crew Male Child No 0

#> 5 1st Female Child No 0

#> 6 2nd Female Child No 0

# 绘制性别与舱位和年龄的关系

ggplot(data = titanic_wide,

aes(axis1 = Class, axis2 = Sex, axis3 = Age,

weight = Freq)) +

scale_x_discrete(limits = c("Class", "Sex", "Age"), expand = c(.1, .05)) +

geom_alluvium(aes(fill = Survived)) +

geom_stratum + geom_text(stat = "stratum", label.strata = TRUE) +

theme_minimal +

ggtitle("passengers on the maiden voyage of the Titanic",

"stratified by demographics and survival")

具体参考说明：data设置数据源，axis设置显示的柱，weight为数值，geom_alluvium为冲击图组间面积连接并按生存率比填充分组，geom_stratum每种有柱状图，geom_text显示柱状图中标签，theme_minimal主题样式的一种，ggtitle设置图标题

图1. 展示性别与舱位和年龄的关系及存活率比例

我们发现上图居然画的是宽表格模式下的数据，而通常ggplot2处理都是长表格模式，如何转换呢？

to_loades转换为长表格

# 长表格模式，to_loades多组组合，会生成alluvium和stratum列。主分组位于命名的key列中

titanic_long <- to_lodes(data.frame(Titanic),

key = "Demographic",

axes = 1:3)

head(titanic_long)

ggplot(data = titanic_long,

aes(x = Demographic, stratum = stratum, alluvium = alluvium,

weight = Freq, label = stratum)) +

geom_alluvium(aes(fill = Survived)) +

geom_stratum + geom_text(stat = "stratum") +

theme_minimal +

ggtitle("passengers on the maiden voyage of the Titanic",

"stratified by demographics and survival")

产生和上图一样的图，只是数据源格式不同。

2. 输入数据格式

定义一种Alluvial宽表格

# 显示数据格式

head(as.data.frame(UCBAdmissions), n = 12)

## Admit Gender Dept Freq

## 1 Admitted Male A 512

## 2 Rejected Male A 313

## 3 Admitted Female A 89

## 4 Rejected Female A 19

## 5 Admitted Male B 353

## 6 Rejected Male B 207

## 7 Admitted Female B 17

## 8 Rejected Female B 8

## 9 Admitted Male C 120

## 10 Rejected Male C 205

## 11 Admitted Female C 202

## 12 Rejected Female C 391

# 判断数据格式

is_alluvial(as.data.frame(UCBAdmissions), logical = FALSE, silent = TRUE)

## [1] "alluvia"

查看性别与专业间关系，并按录取情况分组

ggplot(as.data.frame(UCBAdmissions),

aes(weight = Freq, axis1 = Gender, axis2 = Dept)) +

geom_alluvium(aes(fill = Admit), width = 1/12) +

geom_stratum(width = 1/12, fill = "black", color = "grey") +

geom_label(stat = "stratum", label.strata = TRUE) +

scale_x_continuous(breaks = 1:2, labels = c("Gender", "Dept")) +

scale_fill_brewer(type = "qual", palette = "Set1") +

ggtitle("UC Berkeley admissions and rejections, by sex and department")

3. 三类型间关系，按重点着色

Titanic按生存，性别，舱位分类查看关系，并按舱位填充色

ggplot(as.data.frame(Titanic),

aes(weight = Freq,

axis1 = Survived, axis2 = Sex, axis3 = Class)) +

geom_alluvium(aes(fill = Class),

width = 0, knot.pos = 0, reverse = FALSE) +

guides(fill = FALSE) +

geom_stratum(width = 1/8, reverse = FALSE) +

geom_text(stat = "stratum", label.strata = TRUE, reverse = FALSE) +

scale_x_continuous(breaks = 1:3, labels = c("Survived", "Sex", "Class")) +

coord_flip +

ggtitle("Titanic survival by class and sex")

4. 长表格数据 # to_lodes转换为长表格

UCB_lodes <- to_lodes(as.data.frame(UCBAdmissions), axes = 1:3)

head(UCB_lodes, n = 12)

## Freq alluvium x stratum

## 1 512 1 Admit Admitted

## 2 313 2 Admit Rejected

## 3 89 3 Admit Admitted

## 4 19 4 Admit Rejected

## 5 353 5 Admit Admitted

## 6 207 6 Admit Rejected

## 7 17 7 Admit Admitted

## 8 8 8 Admit Rejected

## 9 120 9 Admit Admitted

## 10 205 10 Admit Rejected

## 11 202 11 Admit Admitted

## 12 391 12 Admit Rejected

# 判断是否符合格式要求

is_alluvial(UCB_lodes, logical = FALSE, silent = TRUE)

## [1] "alluvia"

主要列说明：

• x, 主要的分类，即X轴上每个柱
• stratum, 主要分类中的分组
• alluvium, 连接图的索引

以各国难民数据为例，观察多国难民数量随时间变化

data(Refugees, package = "alluvial")

country_regions <- c(

Afghanistan = "Middle East",

Burundi = "Central Africa",

`Congo DRC` = "Central Africa",

Iraq = "Middle East",

Myanmar = "Southeast Asia",

Palestine = "Middle East",

Somalia = "Horn of Africa",

Sudan = "Central Africa",

Syria = "Middle East",

Vietnam = "Southeast Asia"

)

Refugees$region <- country_regions[Refugees$country]

ggplot(data = Refugees,

aes(x = year, weight = refugees, alluvium = country)) +

geom_alluvium(aes(fill = country, colour = country),

alpha = .75, decreasing = FALSE) +

scale_x_continuous(breaks = seq(2003, 2013, 2)) +

theme(axis.text.x = element_text(angle = -30, hjust = 0)) +

scale_fill_brewer(type = "qual", palette = "Set3") +

scale_color_brewer(type = "qual", palette = "Set3") +

facet_wrap(~ region, scales = "fixed") +

ggtitle("refugee volume by country and region of origin")

6. 等高非等量关系

不同学期学生学习科目的变化

data(majors)

majors$curriculum <- as.factor(majors$curriculum)

ggplot(majors,

aes(x = semester, stratum = curriculum, alluvium = student,

fill = curriculum, label = curriculum)) +

scale_fill_brewer(type = "qual", palette = "Set2") +

geom_flow(stat = "alluvium", lode.guidance = "rightleft",

color = "darkgray") +

geom_stratum +

theme(legend.position = "bottom") +

ggtitle("student curricula across several semesters")

7. 工作状态时间变化图 data(vaccinations)

levels(vaccinations$response) <- rev(levels(vaccinations$response))

ggplot(vaccinations,

aes(x = survey, stratum = response, alluvium = subject,

weight = freq,

fill = response, label = response)) +

geom_flow +

geom_stratum(alpha = .5) +

geom_text(stat = "stratum", size = 3) +

theme(legend.position = "none") +

ggtitle("vaccination survey responses at three points in time") 8. 分类学门水平相对丰度实战 # 实战1. 组间丰度变化

# 编写测试数据

df=data.frame(

Phylum=c("Ruminococcaceae","Bacteroidaceae","Eubacteriaceae","Lachnospiraceae","Porphyromonadaceae"),

GroupA=c(37.7397,31.34317,222.08827,5.08956,3.7393),

GroupB=c(113.2191,94.02951,66.26481,15.26868,11.2179),

GroupC=c(123.2191,94.02951,46.26481,35.26868,1.2179),

GroupD=c(37.7397,31.34317,222.08827,5.08956,3.7393)

)

# 数据转换长表格

library(reshape2)

melt_df = melt(df)

# 绘制分组对应的分类学，有点像circos

ggplot(data = melt_df,

aes(axis1 = Phylum, axis2 = variable,

weight = value)) +

scale_x_discrete(limits = c("Phylum", "variable"), expand = c(.1, .05)) +

geom_alluvium(aes(fill = Phylum)) +

geom_stratum + geom_text(stat = "stratum", label.strata = TRUE) +

theme_minimal +

ggtitle("Phlyum abundance in each group")

绘制分组对应的分类学，有点像circos

# 组间各丰度变化

ggplot(data = melt_df,

aes(x = variable, weight = value, alluvium = Phylum)) +

geom_alluvium(aes(fill = Phylum, colour = Phylum, colour = Phylum),

alpha = .75, decreasing = FALSE) +

theme_minimal +

theme(axis.text.x = element_text(angle = -30, hjust = 0)) +

ggtitle("Phylum change among groups")

组间各丰度变化，如果组为时间效果更好

Reference # 如何引用

citation("ggalluvial")

Jason Cory Brunson (2017). ggalluvial: Alluvial Diagrams in ‘ggplot2’. R package version 0.5.0.

https://CRAN.R-project.org/package=ggalluvial

https://en.wikipedia.org/wiki/Alluvial_diagram

ggalluvial包源码：http://corybrunson.github.io/ggalluvial/index.html

最后编辑：2022-08-20

作者：萌小白

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