复现NC文章华夫图(方块图)-华丽展示实验样本构成
样本构成是实验的开端,也是后续分析的基础,所以样本信息在论文中需要详细展示,涉及到你实验的真实性和可重复性。一般样本构成可以使用AI做示例图,有些临床采样,可以使用柱状体的方式展示,我们之前讲过一种。最近在NC文章中看到用华夫图表示样本的构成,感觉效果很好,这里复现一下。原文图如下:
(Single cell analysis of cribriform prostate cancer reveals cell intrinsic and tumor microenvironmental pathways of aggressive disease)
我的复现结果(一模一样):
根据原图自己设置一个作图文件,很简单,读入文件加载R包:
install.packages("waffle")
library(waffle)
library(ggwaffle)
library(ggplot2)
library(dplyr)
library(tidyverse)
library(reshape2)
library(forcats)
setwd("D:/KS项目/公众号文章/华夫图")
A <- read.csv("华夫图.csv", header = T,
stringsAsFactors = T,
fileEncoding = 'GBK')
数据转化、设置因子顺序:
df=melt(A,id="patient")
df$variable <- as.factor(df$variable)
df$variable <- fct_inorder(df$variable)#x轴因子顺序不变
colnames(df)
df$patient <- as.factor(df$patient)
df$patient <- fct_rev(df$patient)#y轴逆序,保持与文章一致
设定对应颜色:
col_group <- setNames(c("#B5C8E8",
"#4475C7",
"#1A3564",
"#F2B900",
"#FFE79A",
"#CD9AFF",
"#00B1F0",
"#C6E1B5",
"#79B84C"),
c('Grade Group2',
'Grade Group3',
"Grade Group5",
"PSA<10ng/ml",
"PSA>10ng/ml",
"Present",
"Absent",
"≤ pT3a",
"≥ pT3a"))
ggplot结合waffle作图,复刻一模一样:
ggplot(df, aes(variable, patient, fill = value)) +
geom_waffle()+
theme(panel.background = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank(),
legend.title = element_blank(),
legend.position = "right",
axis.text.x = element_text(color = 'black',angle = 45,
size = 12,hjust = 0,vjust = 0.1),
axis.text.y = element_text(color = 'black',size = 12))+
scale_fill_manual("",values = col_group)+
scale_x_discrete(position = "top")+
guides(fill = guide_legend(override.aes = list(size=10),
label.position ='left',
label.theme = element_text(size = 12)))
也可以设置圆形:
ggplot(df, aes(variable, patient, color = value)) +
geom_waffle(tile_shape='circle', size=8)+
theme(panel.background = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank(),
legend.title = element_blank(),
legend.position = "right",
axis.text.x = element_text(color = 'black',angle = 45,
size = 12,hjust = 0,vjust = 0.1),
axis.text.y = element_text(color = 'black',size = 12))+
scale_color_manual("",values = col_group)+
scale_x_discrete(position = "top")+
guides(fill = guide_legend(override.aes = list(size=8),
label.position ='left',
label.theme = element_text(size = 12)))
好了,这就是今天的内容了,作图数据和注释代码已上传群文件!我又突然想起一个事情,这样的方块图也不仅仅展示样本,还可以作为其他图的注释配合使用,真是不错。感兴趣的探索一下,用在自己文章吧!我的公众号--KS科研分享与服务!
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