written in front
[How to draw this picture] The series of pictures are all from VIP群the students' questions. The tweet is only a reproduction of the picture, and does not mean that the author agrees with the form of the picture. Students are welcome to analyze interesting pictures in the group.
Pictures of this issue
❝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
❞
method
The picture shows the prediction results of different subtypes for response to immunotherapy. The data processing in the early stage is cumbersome, so here we start directly from the drawing.
Reproduce results
Sample data and code collection
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drawing
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())
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