一、数据准备

数据使用的不同处理土壤样品的微生物组成数据，包含物种丰度，分类单元和样本分组数据。此数据为虚构，可用于练习，请不要作他用。

# 1.1 设置工作路径
#knitr::opts_knit$set(root.dir="D:\\EnvStat\\PCA")# 使用Rmarkdown进行程序运行
Sys.setlocale('LC_ALL','C') # Rmarkdown全局设置
#options(stringsAsFactors=F)# R中环境变量设置，防止字符型变量转换为因子
setwd("D:\\EnvStat\\alluvial_map")

# 1.2 读入数据
## 物种组成数据
spetax <- read.table("spetax.csv", header=T, row.names=1, sep=",", comment.char="",stringsAsFactors = TRUE,quote = "")
head(spetax)

## 将物种分类单元注释信息与丰度数据分开
spe <- spetax[-c(1:7)]
tax <- spetax[1:7]
head(spe)
head(tax)

## 样本分组数据
group <- read.table("group.csv", header=T, row.names=1, sep=",", comment.char="",stringsAsFactors = TRUE,quote = "")
group$grazing <- factor(group$grazing,levels = c("CK","LG","MG","HG"))
group

图1|物种丰度及分类单元注释信息，spetax.csv。

图2|样本分组信息，group.csv。

二、物种组成冲积图

使用ggalluvial包在门水平绘制物种组成冲积图，可以绘制绝对丰度冲积图，也可以使用相对丰度绘制冲积图。

2.1 绝对丰度物种组成冲积图

# 2.1.1 物种组成数据按照门进行汇总
## spe和tax数据表中物种排序一致
library(tidyverse)
phy <- spe %>%
  group_by(tax$Phylum) %>% # 使用tax中的门水平进行分类
  summarise_all(sum) %>%
  rename(Phylum = `tax$Phylum`) %>%
  gather(key="Samples",value = "abun",-Phylum) %>% # 数据形式转换：“宽”转“长”
  left_join(group,by=c("Samples"="name")) %>%
  select(grazing,depth,Phylum,abun) %>%
  group_by(grazing,depth,Phylum) %>% # 求均值
  summarise_all(mean)
  
dim(phy)
head(phy)

# 2.1.2 颜色
library(ggsci)
col=pal_d3("category20")(20)
col2 = pal_d3("category20",alpha = 0.5)(20)
mypal=c(col,col2[-8])

图3|按门汇总的各处理物种丰度均值数据，phy。long format数据形式可直接用于ggplot2绘图。

# 2.1.3  物种组成冲积图-绝对丰度
abs_allu <- ggplot(data = phy,
       aes(x = depth, y = abun, fill = reorder(Phylum,-abun), 
           stratum = reorder(Phylum,-abun),
           alluvium = reorder(Phylum,-abun))) +
  geom_alluvium()+
    geom_stratum(width=0.45, size=0.1) +
   geom_bar(aes(fill = reorder(Phylum,-abun)),stat='identity', width=0.45) +
  scale_y_continuous(expand=c(0, 0))+
  theme_bw() +
  facet_grid( ~ grazing,scales = "fixed")+
  scale_fill_manual(values = mypal,name="Phylum") +
  scale_color_manual(values = mypal) +
  theme(legend.position = "top",
        panel.grid=element_blank(),
        panel.spacing.x = unit(0,units = "cm"),
        strip.background = element_rect(
     color="white", fill="white", 
     linetype="solid",size=0.8),
     strip.placement = "outside",
     axis.line.y.left = element_line(color="black",size=0.8),
     axis.line.x.bottom = element_line(color="black",size=0.8),
     strip.text.x = element_text(size = 14,face = "bold"),
     axis.text = element_text(face = "bold", 
                                 size = 12,color="black"),
     axis.title = element_text(face = "bold", 
                                  size = 14,colour = "black"),
      legend.title = element_text(face = "bold", 
                                   size =12,color="black"),
    legend.text = element_text(face = "bold", size =12,color="black"),
    axis.ticks.x = element_blank(),
    axis.ticks.y = element_line(size = 0.3),
     
        )+
   labs(x = "Depth",y= "Relative Abundance of Phylum (%)")
abs_allu

ggsave("abs_allu.pdf",abs_allu,device = "pdf",width = 12,height = 8,family="Times")

图4|绝对丰度冲积图，abs_allu.pdf。

2.2 相对丰度物种组成冲积图

# 2.2.1 需要先计算相对丰度
rel_spe <- sweep(spe,2,colSums(spe),'/')*100
head(rel_spe)

# 2.2.2 物种组成数据按照门进行汇总  
## spe和tax数据表中物种排序一致
rel_phy <- rel_spe %>%
  group_by(tax$Phylum) %>% # 使用tax中的门水平进行分类
  summarise_all(sum) %>%
  rename(Phylum = `tax$Phylum`) %>%
  gather(key="Samples",value = "abun",-Phylum) %>% # 数据形式转换：“宽”转“长”
  left_join(group,by=c("Samples"="name")) %>%
  select(grazing,depth,Phylum,abun) %>%
  group_by(grazing,depth,Phylum) %>% # 求均值
  summarise_all(mean)
dim(rel_phy)
head(rel_phy)

图5|按门汇总的各处理物种相对丰度数据，rel_phy。

# 2.2.3  物种组成冲积图-相对丰度
rel_allu <- ggplot(data = rel_phy,
       aes(x = depth, y = abun, fill = reorder(Phylum,-abun), 
           stratum = reorder(Phylum,-abun),
           alluvium = reorder(Phylum,-abun))) +
  geom_alluvium()+
    geom_stratum(width=0.45, size=0.1) +
   geom_bar(aes(fill = reorder(Phylum,-abun)),stat='identity', width=0.45) +
  scale_y_continuous(expand=c(0, 0))+
  theme_bw() +
  facet_grid( ~ grazing,scales = "fixed")+
  scale_fill_manual(values = mypal,name="Phylum") +
  scale_color_manual(values = mypal) +
  theme(legend.position = "top",
        panel.grid=element_blank(),
        panel.spacing.x = unit(0,units = "cm"),
        strip.background = element_rect(
     color="white", fill="white", 
     linetype="solid",size=0.8),
     strip.placement = "outside",
     axis.line.y.left = element_line(color="black",size=0.8),
     axis.line.x.bottom = element_line(color="black",size=0.8),
     strip.text.x = element_text(size = 14,face = "bold"),
     axis.text = element_text(face = "bold", 
                                 size = 12,color="black"),
     axis.title = element_text(face = "bold", 
                                  size = 14,colour = "black"),
      legend.title = element_text(face = "bold", 
                                   size =12,color="black"),
    legend.text = element_text(face = "bold", size =12,color="black"),
    axis.ticks.x = element_blank(),
    axis.ticks.y = element_line(size = 0.3),
     
        )+
   labs(x = "Depth",y= "Relative Abundance of Phylum (%)")
rel_allu

ggsave("rel_allu.pdf",rel_allu,device = "pdf",width = 12,height = 8,family="Times")