写在前面
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本期图片
❝Chen, Hualin et al. “Integrated Analysis Revealed an Inflammatory Cancer-Associated Fibroblast-Based Subtypes with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Bladder Cancer Patients.” International journal of molecular sciences vol. 23,24 15970. 15 Dec. 2022
❞
方法
图片显示不同亚型对免疫治疗反应预测结果。前期数据处理较繁琐，这里就直接从绘图开始。
复现结果
示例数据和代码领取
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绘图
rm(list = ls())
library(ComplexHeatmap)
# submap heatmap
dt <- matrix(runif(3*4*3,0,1),
nrow = 9,byrow = T,
dimnames = list(c("C1","C2","C3",
" C1"," C2"," C3",
" C1"," C2"," C3"),
c("CTAL4-noR","CTLA4-R","PD1-noR","PD1-R")))
hm <- pheatmap(dt,
border_color = "white",
number_format = "%.3f",
cellwidth = 30, cellheight = 30,
cluster_rows = F,cluster_cols = F,
display_numbers = T,
number_color = "black",
fontsize_number = 9,
name = "Statitic",
annotation_row = data.frame(pvalue=c("Nominal p value","Nominal p value","Nominal p value",
"Bonferroni adjusted","Bonferroni adjusted","Bonferroni adjusted",
"FDR adjusted","FDR adjusted","FDR adjusted"),
row.names = rownames(dt)),
annotation_colors = list(pvalue=c("Nominal p value"="black","Bonferroni adjusted"="grey50","FDR adjusted" = "grey80")))
pdf("predicted response to immunotherapy.pdf",width = 5,height = 8)
draw(hm, heatmap_legend_side = "left",annotation_legend_side = "right")
invisible(dev.off())
往期内容
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