R绘图|pheatmap热图绘制——基础篇
2020-06-18 本文已影响0人
Clariom
清除环境及安装R包
rm(list = ls()) #清除环境内存
#install.packages("pheatmap") #安装pheatmap包
#install.packages("readxl") #安装readxl包
#install.packages("ggplot2") #安装ggplot2包
#install.packages(c('officer', 'rvg', 'flextable', 'stargazer', 'broom' ))#export的依赖包
#下载export，链接https://cran.r-project.org/src/contrib/Archive/export/export_0.2.2.tar.gz
#install.packages("D:/R-3.6.2/library/export_0.2.2.tar.gz", repos = NULL)
library(ggplot2)
library(pheatmap) #加载pheatmap包
library(readxl) #加载readxl包
library(export) #用于输出不同格式的结果
读入数据并做简单处理
data<-read_excel("demo1.xlsx",1) #读入excel数据
data<-as.data.frame(data) # 将data转换为data.frame格式
rownames(data)<-data[,1] #将第一列数据设置为行名
data<-data[,-1] #去除重复的第一列
colnames(data) = gsub("_expression","",colnames(data))
head(data)
## CKD1 CKD2 CKD3 CKD4 CKD5 Ctrl1 Ctrl2 Ctrl3 Ctrl4 Ctrl5\r\n
## Fam117b 10.56 10.26 10.99 11.17 11.02 8.28 9.10 9.20 9.34 8.76
## Fkbp5 10.99 10.48 10.89 11.75 10.80 9.44 7.64 8.82 7.92 8.17
## Bcl2l1 9.73 9.50 10.20 9.44 9.98 8.04 8.42 8.77 8.14 7.94
## Zbtb16 12.33 12.36 12.69 11.59 13.21 9.58 10.66 10.11 10.75 9.05
## Fam107a 10.00 9.12 9.21 9.11 8.99 6.99 7.37 6.71 8.15 6.11
## Adrm1 7.50 7.46 7.42 7.80 7.55 6.69 6.69 6.57 6.53 6.83
绘图并输出结果
p=pheatmap(data,fontsize_col=9,fontsize_row=8,
show_rownames=F,show_colnames = T,
cluster_row=T,cluster_col=T,scale="row",
treeheight_row=25,treeheight_col=25,
border_color=NA,main="Heatmap") # 画图
print(p)
image
ggsave(p,filename = "pheatmap.pdf",width=6,height=8)
ggsave(p,filename = "pheatmap.png",width=6,height=8)
#也可以加载export包输出结果
#graph2pdf(file="pheatmap.pdf",width=6,height=8)#导出pdf格式文件
#graph2tif(file="pheatmap.tif",width=6,height=8)#导出tiff格式文件
#graph2jpg(file="pheatmap.jpg",width=6,height=8)#导出jpg格式文件
颜色设置
修改热图颜色1
p1=pheatmap(data,fontsize_col=9,fontsize_row=8,
show_rownames=F,show_colnames = T,
cluster_row=T,cluster_col=T,scale="row",
treeheight_row=25,treeheight_col=25,
border_color=NA,main="Heatmap",
color = colorRampPalette(c("green", "black", "red"))(50)) # 画图
print(p1)
image
ggsave(p,filename = "demo1_1.pdf",width=6,height=8)
ggsave(p,filename = "demo1_1.png",width=6,height=8)
修改热图颜色2
p2=pheatmap(data,fontsize_col=9,fontsize_row=8,
show_rownames=F,show_colnames = T,
cluster_row=T,cluster_col=T,scale="row",
treeheight_row=25,treeheight_col=25,
border_color=NA,main="Heatmap",
color = colorRampPalette(c("blue", "white", "red"))(50)) # 画图
print(p2)
image
ggsave(p2,filename = "demo1_2.pdf",width=6,height=8)
ggsave(p2,filename = "demo1_2.png",width=6,height=8)
修改热图颜色3
p3=pheatmap(data,fontsize_col=9,fontsize_row=8,
show_rownames=F,show_colnames = T,
cluster_row=T,cluster_col=T,scale="row",
treeheight_row=25,treeheight_col=25,
border_color=NA,main="Heatmap",
color = colorRampPalette(c("blue", "white", "yellow"))(50)) # 画图
print(p3)
image.png
ggsave(p3,filename = "demo1_3.pdf",width=6,height=8)
ggsave(p3,filename = "demo1_3.png",width=6,height=8)
显示基因名称
以上数据非常多，选择部分数据绘图
library(pheatmap) #加载pheatmap包
library(readxl) #加载readxl包
data<-read_excel("demo1.xlsx",1) #读入excel数据
data<-as.data.frame(data) # 将data转换为data.frame格式
rownames(data)<-data[,1] #将第一列数据设置为行名
data<-data[,-1] #去除重复的第一列
data_part<-head(data,15) #取前15行进一步绘图
colnames(data_part) = gsub("_expression","",colnames(data_part))# 设置列名
p4=pheatmap(data_part,
fontsize_col=9,fontsize_row=8,
show_rownames=T,show_colnames = T,
cluster_row=T,cluster_col=T,scale="row",
treeheight_row=25,treeheight_col=25,
border_color=NA,main="Heatmap",
color = colorRampPalette(c("blue", "white", "yellow"))(50)) # 画图
print(p4)
image
ggsave(p4,filename = "demo1_4.pdf",width=6,height=8)
ggsave(p4,filename = "demo1_4.png",width=6,height=8)
调整格子大小并显示数值
p5=pheatmap(data_part,fontsize_col=9,fontsize_row=8,
show_rownames=T,show_colnames = T,
cluster_row=T,cluster_col=T,scale="row",
treeheight_row=25,treeheight_col=25,
border_color=NA,main="Heatmap",
color = colorRampPalette(c("blue", "white", "yellow"))(50),
display_numbers = TRUE,
cellwidth = 30, cellheight = 30) # 画图
print(p5)
image
ggsave(p5,filename = "demo1_5.pdf",width=6,height=8)
ggsave(p5,filename = "demo1_5.png",width=6,height=8)
显示运行环境
sessionInfo()
## R version 3.6.2 (2019-12-12)
## 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] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] export_0.2.2 readxl_1.3.1 pheatmap_1.0.12 ggplot2_3.2.1
##
## loaded via a namespace (and not attached):
## [1] rgl_0.100.50 Rcpp_1.0.3 lattice_0.20-38
## [4] tidyr_1.0.2 assertthat_0.2.1 digest_0.6.24
## [7] mime_0.9 R6_2.4.1 cellranger_1.1.0
## [10] backports_1.1.5 evaluate_0.14 pillar_1.4.3
## [13] gdtools_0.2.1 rlang_0.4.4 lazyeval_0.2.2
## [16] uuid_0.1-4 miniUI_0.1.1.1 data.table_1.12.8
## [19] flextable_0.5.9 rmarkdown_2.1 webshot_0.5.2
## [22] stringr_1.4.0 htmlwidgets_1.5.1 munsell_0.5.0
## [25] shiny_1.4.0 broom_0.5.5 compiler_3.6.2
## [28] httpuv_1.5.2 xfun_0.12 pkgconfig_2.0.3
## [31] systemfonts_0.1.1 base64enc_0.1-3 rvg_0.2.4
## [34] htmltools_0.4.0 tidyselect_1.0.0 tibble_2.1.3
## [37] crayon_1.3.4 dplyr_0.8.4 withr_2.1.2
## [40] later_1.0.0 grid_3.6.2 nlme_3.1-142
## [43] jsonlite_1.6.1 xtable_1.8-4 gtable_0.3.0
## [46] lifecycle_0.1.0 magrittr_1.5 scales_1.1.0
## [49] zip_2.0.4 stringi_1.4.6 promises_1.1.0
## [52] xml2_1.2.2 vctrs_0.2.3 generics_0.0.2
## [55] openxlsx_4.1.4 stargazer_5.2.2 RColorBrewer_1.1-2
## [58] tools_3.6.2 manipulateWidget_0.10.1 glue_1.3.1
## [61] officer_0.3.8 purrr_0.3.3 crosstalk_1.0.0
## [64] fastmap_1.0.1 yaml_2.2.1 colorspace_1.4-1
## [67] knitr_1.28
往期回顾
R绘图|ggplot2散点图的绘制
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