使用ggplot绘制柱状图，在柱子中显示数值和显著性
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### 本期教程
**获得本期教程示例数据，后台回复关键词：「20240628」。（PS：在社群中，可获得往期和未来教程所有数据和代码）**
### 往期教程部分内容
## 写在前面
**基于ggplot绘制柱状图，小技巧，很基础的图形。但是，越到后面，会发现，越是基础的图形，我们使用的频率越高。今天的教程是基于发芽指数来绘制，我们模拟一个发芽数和天数，计算出发芽指数。**
### 代码
```plain
##'@在柱状图中显示数字
##'@2024.06.28
##'@
##'@小杜的生信笔记
library(ggplot2)
library(dplyr)
library(tidyr)
library(ggplot2)
library(agricolae)
setwd("D:\\BioinfoFile\\小杜的生信笔记\\2024\\20240628_柱状图中显示数据")
##'@此次数据基于种子发芽指数计算公式进行，数据具有随机性，不具有任何意义。
##'@加载数据
data <- read.csv("20240628_inputdata.csv",header = T)
data
```
**「相关计算代码」**
```plain
## 转换数据
long_data <- data %>%
pivot_longer(cols = starts_with("germinated"), names_to = "replicate", values_to = "germinated")
long_data
##计算活力指数
germination_index <- long_data %>%
group_by(treatment, day) %>%
summarise(GI = sum(germinated / day)) %>%
ungroup()
#'@计算各个处理的平均数和标准差
summary_gi <- germination_index %>%
group_by(treatment) %>%
summarise(mean_GI = mean(GI), sd_GI = sd(GI))
#'@单因素方差分析
anova_result <- aov(GI ~ treatment + day, data = germination_index)
summary(anova_result)
#'@进行Tukey HSD检验
tukey_result <- HSD.test(anova_result, "treatment", group = TRUE)
print(tukey_result)
# 提取 Tukey HSD 结果中的字母标记
groups <- tukey_result$groups
df_letters <- data.frame(sample = rownames(groups), letters = groups$groups)
##'@修改名称
colnames(df_letters) <- c("treatment","letters")
# 合并均值和字母标记
df_data <- merge(summary_gi, df_letters, by = "treatment")
```
### 绘图
```plain
ggplot(df_data, aes(x = treatment, y = mean_GI, fill = treatment)) +
geom_bar(stat = "identity", position = "dodge", color = "black", size = 0.5) +
##'@误差线
geom_errorbar(aes(ymin = mean_GI - sd_GI, ymax = mean_GI + sd_GI), width = 0.15, ## 宽度
size = 1##字体大小
) +
##'@显示数字
geom_text(aes(x = treatment, y = mean_GI + sd_GI + 0.5,## “+0.5”显示的高度
label = round(mean_GI, 2)), ### "round(mean_GI, 2))",其中2，表示数字显示的小数点位数
size = 5,
color = 'black') +
##'@显示显著性
geom_text(aes(x = treatment, y = mean_GI + sd_GI + 1.3, label = letters), size = 6, color = "red") +
theme_bw()+
scale_fill_manual(values = c("#1f78b4", "#ff7f00", "#4daf4a")) +
labs(x = NULL, y = "Germination Index")+
theme(#axis.line = element_line(size = 1),## 粗细
text=element_text(#family = "sans",
colour ="black",size = 10),
axis.text.x = element_text(color = "black", size = 12),
axis.text.y = element_text(color = "black",size = 11),
axis.ticks = element_line(colour = "black"),
strip.text = element_text(color = "black",size = 10),
axis.title = element_text(color = "black",size = 12), ##坐标轴字体大小
legend.position = "none",
strip.background = element_blank()
)
ggsave("20240608_柱状图-显示数字.pdf",width = 6, height = 4)
```
**获得本期教程示例数据，后台回复关键词：「20240628」。（PS：在社群中，可获得往期和未来教程所有数据和代码）**
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### 往期部分文章
**「1. 最全WGCNA教程（替换数据即可出全部结果与图形）」**
* (https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455850466&idx=1&sn=6036fc2a19594f7fc38d65271f21e9cc&scene=21#wechat_redirect)
* (https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455850727&idx=1&sn=1156c2bb0b0c9baff02838f5ffce39bf&scene=21#wechat_redirect)
* (https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455850742&idx=1&sn=3d3eeedb3b58e536a83dc38d15725cd4&scene=21#wechat_redirect)
* (https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455854728&idx=5&sn=bc98befb8dd0f0090bdfe69f3ffdb008&scene=21#wechat_redirect)
* (https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455856103&idx=1&sn=774f8a084d21f757266f35c501c7155d&scene=21#wechat_redirect)
---
**「2. 精美图形绘制教程」**
* [精美图形绘制教程](https://mp.weixin.qq.com/mp/appmsgalbum?__biz=MzAwODY5NDU0MA==&action=getalbum&album_id=2614156000866385923&scene=173&from_msgid=2455848496&from_itemidx=1&count=3&nolastread=1#wechat_redirect)
**「3. 转录组分析教程」**
* **「**[转录组上游分析教程[零基础]](https://mp.weixin.qq.com/mp/appmsgalbum?__biz=MzAwODY5NDU0MA==&action=getalbum&album_id=2870608342451224581&scene=126&uin=&key=&devicetype=Windows+10+x64&version=63090719&lang=zh_CN&ascene=0)**」**
* **「**[一个转录组上游分析流程 | Hisat2-Stringtie](https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455857417&idx=1&sn=653f3bdb0af386c22a128732ec8a01a4&scene=21#wechat_redirect)**」**
**「4. 转录组下游分析」**
* [批量做差异分析及图形绘制 | 基于DESeq2差异分析](https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455860684&idx=1&sn=7be489c453cca737ad1092c6e4499827&scene=21#wechat_redirect)
* (https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455859512&idx=1&sn=bac01a018f8b58afc7e2b3484f476bf4&scene=21#wechat_redirect)
* [单基因GSEA富集分析](https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455859147&idx=1&sn=b022d80868e4b8014f64d443c82d1668&scene=21#wechat_redirect)
* [全基因集GSEA富集分析](https://mp.weixin.qq.com/s?__biz=MzAwODY5NDU0MA==&mid=2455860201&idx=1&sn=dd65c5b967123a876a6f5a38d4723ca6&scene=21#wechat_redirect)
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