09.韦恩图绘制
清除当前环境中的变量
rm(list=ls())
设置工作目录
setwd("C:/Users/Dell/Desktop/R_Plots/09venndiagram/")
gplots包绘制韦恩图
library(gplots)
##
## Attaching package: 'gplots'
## The following object is masked from 'package:stats':
##
## lowess
data <- read.table("demo1_venn.txt", header = T, sep = "\t")
head(data)
## Set1 Set2 Set3 Set4 Set5
## 1 ZMIZ1 ADCY5 TNS1 TNS1 TNS1
## 2 TNS1 ACTN4 ZMIZ1 ZMIZ1 ZMIZ1
## 3 CASZ1 SORBS1 RXRA RXRA TSPAN9
## 4 NFIC TNS1 AHDC1 NCOR2 MIDN
## 5 CACNA1C ZMIZ1 ACTN4 MIDN NCOR2
## 6 AHDC1 RBM20 MIDN AHDC1 AHDC1
attach(data)
# 绘制二维韦恩图
venn(data = list(Set1,Set2))
image.png
# 绘制三维韦恩图
venn(data = list(Set1,Set2,Set3))
image.png
# 绘制四维韦恩图
venn(data = list(Set1,Set2,Set3,Set4))
image.png
# 绘制五维韦恩图
venn(data = list(Set1,Set2,Set3,Set4,Set5))
image.png
VennDiagram包绘制韦恩图
library(VennDiagram)
## Loading required package: grid
## Loading required package: futile.logger
# 使用draw.single.venn函数绘制一维韦恩图
venn.plot <- draw.single.venn(
area = 365,
category = "All\nDays",
lwd = 5,
lty = "blank",
cex = 3,
label.col = "orange",
cat.cex = 4,
cat.pos = 180,
cat.dist = -0.20,
cat.col = "white",
fill = "red",
alpha = 0.15
);
grid.newpage();
image.png
# 使用draw.pairwise.vennh函数绘制二维韦恩图
venn.plot <- draw.pairwise.venn(
area1 = 100,
area2 = 70,
cross.area = 68,
category = c("First", "Second"),
fill = c("blue", "red"),
lty = "blank",
cex = 2,
cat.cex = 2,
cat.pos = c(285, 105),
cat.dist = 0.09,
cat.just = list(c(-1, -1), c(1, 1)),
ext.pos = 30,
ext.dist = -0.05,
ext.length = 0.85,
ext.line.lwd = 2,
ext.line.lty = "dashed"
);
grid.newpage();
image.png
# 使用draw.triple.vennh函数绘制三维韦恩图
venn.plot <- draw.triple.venn(
area1 = 65,
area2 = 75,
area3 = 85,
n12 = 35,
n23 = 15,
n13 = 25,
n123 = 5,
category = c("First", "Second", "Third"),
fill = c("blue", "red", "green"),
lty = "blank",
cex = 2,
cat.cex = 2,
cat.col = c("blue", "red", "green")
);
grid.newpage();
image.png
# 使用draw.quad.venn函数绘制四维韦恩图
# Reference four-set diagram
venn.plot <- draw.quad.venn(
area1 = 72,
area2 = 86,
area3 = 50,
area4 = 52,
n12 = 44,
n13 = 27,
n14 = 32,
n23 = 38,
n24 = 32,
n34 = 20,
n123 = 18,
n124 = 17,
n134 = 11,
n234 = 13,
n1234 = 6,
category = c("First", "Second", "Third", "Fourth"),
fill = c("orange", "red", "green", "blue"),
lty = "dashed",
cex = 2,
cat.cex = 2,
cat.col = c("orange", "red", "green", "blue")
);
grid.newpage();
image.png
# 使用draw.quintuple.venn函数绘制五维韦恩图
# Reference five-set diagram
venn.plot <- draw.quintuple.venn(
area1 = 301,
area2 = 321,
area3 = 311,
area4 = 321,
area5 = 301,
n12 = 188,
n13 = 191,
n14 = 184,
n15 = 177,
n23 = 194,
n24 = 197,
n25 = 190,
n34 = 190,
n35 = 173,
n45 = 186,
n123 = 112,
n124 = 108,
n125 = 108,
n134 = 111,
n135 = 104,
n145 = 104,
n234 = 111,
n235 = 107,
n245 = 110,
n345 = 100,
n1234 = 61,
n1235 = 60,
n1245 = 59,
n1345 = 58,
n2345 = 57,
n12345 = 31,
category = c("A", "B", "C", "D", "E"),
fill = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
cat.col = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
cat.cex = 2,
margin = 0.05,
cex = c(1.5, 1.5, 1.5, 1.5, 1.5, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8,
1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 1, 1, 1, 1, 1.5),
ind = TRUE
);
grid.newpage();
# Writing to file
tiff(filename = "Quintuple_Venn_diagram.tiff", compression = "lzw");
grid.draw(venn.plot);
dev.off();
image.png
# 使用venn.diagram函数绘制韦恩图
data <- read.table("demo1_venn.txt", header = T, sep = "\t")
head(data)
## Set1 Set2 Set3 Set4 Set5
## 1 ZMIZ1 ADCY5 TNS1 TNS1 TNS1
## 2 TNS1 ACTN4 ZMIZ1 ZMIZ1 ZMIZ1
## 3 CASZ1 SORBS1 RXRA RXRA TSPAN9
## 4 NFIC TNS1 AHDC1 NCOR2 MIDN
## 5 CACNA1C ZMIZ1 ACTN4 MIDN NCOR2
## 6 AHDC1 RBM20 MIDN AHDC1 AHDC1
attach(data)
## The following objects are masked from data (pos = 6):
##
## Set1, Set2, Set3, Set4, Set5
# 一维韦恩图
venn.plot <- venn.diagram(
x = list(Set1=Set1),
filename = NULL,
col = "black",
lwd = 9,
fontface = "bold",
fill = "grey",
alpha = 0.75,
cex = 4,
cat.cex = 3,
cat.fontface = "bold",
);
grid.draw(venn.plot);
grid.newpage();
image.png
# 二维韦恩图
venn.plot <- venn.diagram(
x = list(Set1=Set1,Set2=Set2),
filename = NULL,
lwd = 4,
fill = c("cornflowerblue", "darkorchid1"),
alpha = 0.75,
label.col = "white",
cex = 4,
fontfamily = "serif",
fontface = "bold",
cat.col = c("cornflowerblue", "darkorchid1"),
cat.cex = 3,
cat.fontfamily = "serif",
cat.fontface = "bold",
cat.dist = c(0.03, 0.03),
cat.pos = c(-20, 14)
);
grid.draw(venn.plot);
grid.newpage();
image.png
# 三维韦恩图
venn.plot <- venn.diagram(
x = list(Set1=Set1,Set2=Set2,Set3=Set3),
filename = NULL,
col = "transparent",
fill = c("red", "blue", "green"),
alpha = 0.5,
label.col = c("darkred", "white", "darkblue", "white",
"white", "white", "darkgreen"),
cex = 2.5,
fontfamily = "serif",
fontface = "bold",
cat.default.pos = "text",
cat.col = c("darkred", "darkblue", "darkgreen"),
cat.cex = 2.5,
cat.fontfamily = "serif",
cat.dist = c(0.06, 0.06, 0.03),
cat.pos = 0
);
grid.draw(venn.plot);
grid.newpage();
image.png
# 四维韦恩图
venn.plot <- venn.diagram(
x = list(Set1=Set1,Set2=Set2,Set3=Set3,Set4=Set4),
filename = NULL,
col = "black",
lty = "dotted",
lwd = 4,
fill = c("cornflowerblue", "green", "yellow", "darkorchid1"),
alpha = 0.50,
label.col = c("orange", "white", "darkorchid4", "white", "white", "white",
"white", "white", "darkblue", "white",
"white", "white", "white", "darkgreen", "white"),
cex = 2.5,
fontfamily = "serif",
fontface = "bold",
cat.col = c("darkblue", "darkgreen", "orange", "darkorchid4"),
cat.cex = 2.5,
cat.fontfamily = "serif"
);
grid.draw(venn.plot);
grid.newpage();
image.png
# 五维韦恩图
venn.plot <- venn.diagram(
x = list(Set1=Set1,Set2=Set2,Set3=Set3,Set4=Set4,Set5=Set5),
filename = NULL,
col = "black",
fill = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
alpha = 0.50,
cex = c(1.5, 1.5, 1.5, 1.5, 1.5, 1, 0.8, 1, 0.8, 1, 0.8, 1, 0.8,
1, 0.8, 1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 0.55, 1, 1, 1, 1, 1, 1.5),
cat.col = c("dodgerblue", "goldenrod1", "darkorange1", "seagreen3", "orchid3"),
cat.cex = 1.5,
cat.fontface = "bold",
margin = 0.05
);
grid.draw(venn.plot);
grid.newpage();
image.png
sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 18363)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936
## [2] LC_CTYPE=Chinese (Simplified)_China.936
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C
## [5] LC_TIME=Chinese (Simplified)_China.936
##
## attached base packages:
## [1] grid stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] VennDiagram_1.6.20 futile.logger_1.4.3 gplots_3.0.1.1
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.1 gtools_3.8.1 digest_0.6.20
## [4] bitops_1.0-6 futile.options_1.0.1 formatR_1.7
## [7] magrittr_1.5 evaluate_0.14 KernSmooth_2.23-15
## [10] stringi_1.4.3 gdata_2.18.0 rmarkdown_1.13
## [13] lambda.r_1.2.3 tools_3.6.0 stringr_1.4.0
## [16] xfun_0.8 yaml_2.2.0 compiler_3.6.0
## [19] caTools_1.17.1.2 htmltools_0.3.6 knitr_1.23