R语言:ggplot2做柱状图,随机生成颜色。

时间:2024-03-20 09:15:31

#加载包

> library(ggplot2)
> library(tidyverse)
> library(openxlsx)
> library(reshape2)
> library(RColorBrewer)
> library(randomcoloR)
> library(viridis)
> set.seed(1233)   #设立种子数。
> palette <- distinctColorPalette(30) #生成随机30个颜色。

> write.table(palette, file = "30genus color.txt", sep = ",") #记录随机生成的颜色

> setwd("设立目录")
> mydata <- read.xlsx("读取.xlsx")
> data_draw<-melt(mydata,id.vars='species')#转换数据

> head(mydata)
                   species      T1     T2     T3     T4      T5     T6     T7     T8     T9
1 Streptococcus salivarius   44092 121843 311183 486756 1156014 223453 163548  31383  47748
2      Rothia mucilaginosa  389451 347085 151944 159476  249279  92135 405152  99208 347259
3   Haemophilus influenzae 1051110 597710      0      0       0      0      0      0   2878
4      Streptococcus mitis  382851 246140 103352 211729   86955  18720 142086 416849   3792
5      Gemella haemolysans  109751  63687  15401 159620   15844   1537 194576 691594  64046
6 Streptococcus pneumoniae  180474 106915  78916  85142   49947  10830 313821 300134      0
> head(data_draw)
                   species variable   value
1 Streptococcus salivarius       T1   44092
2      Rothia mucilaginosa       T1  389451
3   Haemophilus influenzae       T1 1051110
4      Streptococcus mitis       T1  382851
5      Gemella haemolysans       T1  109751
6 Streptococcus pneumoniae       T1  180474

 > data_draw$species <- factor(data_draw$species, levels = c("Streptococcus salivarius", "Rothia mucilaginosa", "Haemophilus influenzae", "Streptococcus mitis",
"Gemella haemolysans", "Streptococcus pneumoniae", "Streptococcus parasanguinis", "Neisseria mucosa",
"Streptococcus oralis", "Haemophilus parainfluenzae", "Neisseria subflava", "Neisseria sicca", "Fusobacterium nucleatum",
"Prevotella melaninogenica", "Neisseria flavescens", "Veillonella parvula", "Veillonella dispar",
"Gemella sanguinis", "Streptococcus gordonii", "Leptotrichia wadei", "Streptococcus cristatus",
"Streptococcus anginosus", "Gemella morbillorum", "Neisseria meningitidis", "Veillonella atypica",
"Streptococcus sanguinis", "Corynebacterium argentoratense", "Streptococcus australis",
"Lactobacillus crispatus", "others"))#对种类图形元素排序,保证图形是从大向小排。

> ggplot(data_draw, aes(x = variable, y = value)) +
  geom_bar(aes(fill = species), stat = "identity", color = NA, size = 0.4,
           position = "fill", alpha = 0.90, width = 0.9) +
  scale_fill_manual(values = palette) +
  labs(y = "Relative abundance", x = "Sample") +
  theme(
    text = element_text(family = 'serif'),
    axis.title = element_text(size = 14, face = "plain", color = "black"),
    axis.text = element_text(size = 14, face = "plain", color = "black"),
    legend.title = element_text(size = 14, face = "bold", color = "black"),
    panel.background = element_blank(),
    axis.line = element_line(colour = "black", size = 0.4),
    legend.position = "right", # 在这里设置图例位置
  ) +
  scale_y_continuous(expand = c(0, 0)) +
  theme(
    plot.margin = unit(c(2, 1, 1, 1), "lines"),
    axis.ticks.length = unit(0.1, "cm"),
    axis.text.x = element_text(margin = unit(c(0.5, 0.5, 0.5, 0.5), "cm")),
    axis.text.y = element_text(margin = unit(c(0.5, 0.5, 0.5, 0.5), "cm"))
  )

这种方法是直接将数据处理好,再导入R语言的。