柱狀圖-腫瘤某一指標的比較和GSVA結(jié)果展示
爾云間? 一個專門做科研的團隊
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本篇將介紹如何利用ggplot2繪制柱狀圖以清楚地展示各腫瘤某一指標的比較（如腫瘤緩解率）和GSVA分析結(jié)果。
1、腫瘤緩解率結(jié)果展示
首先啟動程序包
library(ggplot2)
然后讀取數(shù)據(jù)
df<-read.csv("easy_input1.csv")
數(shù)據(jù)結(jié)構(gòu)如下圖，為2列。第一列為不同癌癥，第二列為score
按照score排序，并畫圖：
df<-df[order(df$score,decreasing = T),]
df$index<-seq(1,nrow(df))
p<-ggplot(df,aes(x=index,y=score,fill=ID)) +
? geom_bar(stat = 'identity',width = 0.8) +
? scale_fill_brewer(type = "Qualitative", palette = "Paired") + #bar的顏色
?
? scale_y_continuous(breaks=seq(-100, 100, 10), #y軸刻度
???????????????????? expand = c(0,0)) + #上下都不留空
? scale_x_discrete(expand = expand_scale(mult = c(0.01,0))) + #左邊留空，右邊到頭
? #畫3條橫線
? geom_hline(yintercept = c(-30,0,20),
???????????? linetype = 5, #畫虛線
???????????? size = 0.3) + #線的粗細
?
? #其他主題
? labs(x = "", y = "Maximum Change in Tumor Size (%)",
?????? title = "A Maximum Change in Tumor Size, According to Tumor Type") +
? theme_bw() + #去除背景色
? theme(panel.grid =element_blank()) + #去除網(wǎng)格線
? theme(panel.border = element_blank()) + #去除外層邊框
? theme(axis.line = element_line(colour = "black")) + #沿坐標軸顯示直線
? theme(axis.line.x = element_blank(), axis.ticks.x = element_blank(), axis.text.x = element_blank()) + #去除x軸
?
? #圖例
? guides(fill = guide_legend(ncol = 5,title = NULL)) + #圖例分5列
? scale_size(range=c(5,20)) +
? theme(legend.background = element_blank(), #移除整體邊框
??????? #圖例的左下角置于繪圖區(qū)域的左下角
??????? legend.position=c(0,0),legend.justification = c(0,0))
??????? #改用下面這行，圖例就會位于頂部
??????? #legend.position="top")
由于Cancer12值很高，使得圖片右側(cè)很空。對其進行修改，讓y軸適合大部分數(shù)據(jù)，然后在最高的那個bar上標出實際數(shù)據(jù)。
#設(shè)置坐標軸范圍，最大值設(shè)為50，以適應(yīng)大多數(shù)數(shù)據(jù)
P <- p + coord_cartesian(ylim = c(-90,50)) + #y軸范圍，根據(jù)實際情況調(diào)整
? #添加數(shù)據(jù)標簽
? geom_text(data = subset(df, score > 50),
??????????? aes(index, 48,label=round(score))) + #在超過50的bar上標出實際數(shù)據(jù)
? geom_text(data = subset(df, index == 3),
??????????? aes(index, score + 1,label = "*")) + #作者的特殊標記
? geom_text(data = subset(df, index == nrow(df)),
??????????? aes(index, score - 3, label = "T"))? #作者的特殊標記
2、GSVA結(jié)果展示
2.1 score絕對值小于閾值的bar顯示為灰色
輸入數(shù)據(jù)，包含兩列：ID和score
df<-read.csv("easy_input2.csv")
按照score的值分組
df$group<-cut(df$score, breaks = c(-Inf,-4,4,Inf),labels = c(1,2,3))
按照score排序
df<-df[order(df$score,decreasing = F),]
df$index<-seq(1,nrow(df))
開始畫圖：
ggplot(df,aes(x=index,y=score,fill=group)) +
? geom_bar(stat = 'identity',width = 0.8) +
? scale_fill_manual(values = c("palegreen3","snow3","dodgerblue4")) + #bar的顏色
? scale_x_discrete(expand = expand_scale(add = .6)) +
? scale_y_continuous(breaks=seq(-30, 20, 5)) +
? coord_flip() + #坐標軸互換
?
? #畫2條橫線
? geom_hline(yintercept = c(-4,4),
???????????? color="white",
???????????? linetype = 2,#畫虛線
???????????? size = 0.3) + #線的粗細
? #寫label
? geom_text(data = subset(df, score > 0),
??????????? aes(x=index, y=0, label=paste0(ID,"? "), color = group),#bar跟坐標軸間留出間隙
??????????? size = 3, #字的大小
??????????? hjust = "inward" ) +? #字的對齊方式
? geom_text(data = subset(df, score < 0),
??????????? aes(x=index, y=0, label=paste0("? ",ID), color = group),
??????????? size = 3, hjust = "outward") + ?
? scale_colour_manual(values = c("black","snow3","black")) +
? #其他主題
? labs(x = "", y = "t value of GSVA score, tumor \n versus non-malignant",
?????? title = "Endothelial cells, tumour versus non-malignant") +
? theme_bw() + #去除背景色
? theme(panel.grid =element_blank()) + #去除網(wǎng)格線
? theme(panel.border = element_rect(size = 0.6)) + #邊框粗細
? theme(axis.line.y = element_blank(), axis.ticks.y = element_blank(), axis.text.y = element_blank()) + #去除y軸
? guides(fill=FALSE,color=FALSE)? #不顯示圖例
2.2 pvalue>0.05的bar顯示為灰色
輸入數(shù)據(jù)，包含三列，ID、score和pvalue
df<-read.csv("easy_input3.csv")
#按照pvalue分組
df$p.group<-cut(df$pval, breaks = c(-Inf,0.05,Inf),labels = c(1,0))
#按照score分組
df$s.group<-cut(df$score, breaks = c(-Inf,0,Inf),labels = c(0,1))
#合并
df$ps.group <- paste0(df$p.group,df$s.group)
#根據(jù)pvalue和score分為3組
df$group<-ifelse(df$ps.group=='10','1',ifelse(df$ps.group=='11','2','3'))
按照score排序
df<-df[order(df$score,decreasing = F),]
df$index<-seq(1,nrow(df))
開始畫圖：
只調(diào)整了顏色順序，其余跟“2.1”的畫圖代碼是一樣的
scale_fill_manual(values = c("palegreen3","dodgerblue4","snow3")) + #顏色
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