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自定义颜色
rm(list=ls())
pacman::p_load(tidyverse,magrittr,reshape,RColorBrewer,ggalluvial)
colors <-c("#E41A1C","#1E90FF","#FF8C00","#4DAF4A","#984EA3",
"#40E0D0","#FFC0CB","#00BFFF","#FFDEAD","#90EE90",
"#EE82EE","#00FFFF","#F0A3FF", "#0075DC",
"#993F00","#4C005C","#2BCE48","#FFCC99",
"#808080","#94FFB5","#8F7C00","#9DCC00",
"#426600","#FF0010","#5EF1F2","#00998F",
"#740AFF","#990000","#FFFF00")
自定义主题
theme_niwot <- function(){
theme(text = element_text(family = "Times"),
axis.line.x = element_line(color="black"),
axis.line.y = element_line(color="black"),
axis.text.x = element_text(family = "Times",size=12,face="plain"),
axis.text.y = element_text(family = "Times",size=12,face="plain"),
panel.border = element_blank(),
axis.title.x = element_text(margin = margin(t = 10),size=13,
family = "Times",color="black"),
axis.title.y = element_text(margin = margin(r = 10),size=13,
family = "Times",color="black"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.y = element_blank(),
plot.margin = unit(c(1, 1, 1, 1), units = ,"cm"),
legend.text = element_text(size = 12,family ="Times"),
legend.key = element_blank(),
panel.background = element_rect(fill = "white"),
legend.background = element_rect(color = "black",
fill = "transparent",size = 2, linetype = "blank"))+
theme_bw()+theme(legend.title = element_blank())
}
自定义函数对数据进行过滤
computed_persent <- function(path) {
data <- path %>%
read.delim(check.names = FALSE, row.names = 1)
data2 <- data %>%
mutate(sum = rowSums(.), persent = sum / sum(sum) * 100, sum = NULL,) %>%
rbind(filter(., persent < 1) %>% colSums()) %>%
mutate(ID = c(data %>% rownames(), "others"))
filter(data2[1:(nrow(data2) - 1),], persent > 1) %>%
rbind(data2[nrow(data2),]) %>%
set_rownames(seq_len(nrow(.))) %>%
return()
}
计算百分比，将占比低于1%的归类的others中
将数据跟分组文件整合
path <- "genus.xls" #此处写入的是文件路径
a1 <- computed_persent(path) %>% melt() %>% filter(variable !="persent")
a2 <- "group.txt" %>% read.delim()
a4 <- NULL
for (i in seq_len(nrow(a1))) {
a4[i] <- a2[which(a2[, 1] == a1[i, 2]),2] }
a1[,4] <- a4
> head(a1)
ID variable value V4
1 Aeromonas B1 144 B
2 Bacteroides B1 282 B
3 Barnesiellaceae_uncultured B1 34 B
4 Bradyrhizobium B1 928 B
5 Brevundimonas B1 414 B
6 Cetobacterium B1 550 B
ggplot2进行数据可视化
ggplot(a1,aes(variable,value,alluvium=ID,stratum = ID))+
geom_alluvium(aes(fill = ID),alpha = .5,width = 0.6) +
geom_stratum(aes(fill = ID),width = 0.6)+
facet_grid(. ~V4,scales = "free",space="free_x")+
labs(x=NULL,y=NULL)+
scale_fill_manual(values = colors)+
scale_y_continuous(expand=c(0,0))+
theme_niwot()
