linshi <- linshi[names(score),]
annotation_col <- annotation_col[names(score),]
annotation_col$ImmlncRNAscore <- factor(c(rep(“low”,3126),rep(“high”,5880)))
ann_colors = list(
ImmlncRNAscore = c(“low” = lowblue, “high” = highred),
cluster = c( “imm hot”= red1, “imm balance” = green),
stage = c(‘I/II’ = danblue, ‘III/IV’ = pink, ‘NaN’ = ‘grey’)

)

linshi <- t(linshi)
p <- pheatmap(linshi,fontsize=8,
color = colorRampPalette(c(blue,white,red))(100),
annotation_col = annotation_col,
annotation_colors = ann_colors,
clustering_method = “ward.D2”,
border_color = “grey60”,
clustering_distance_cols = “correlation”,
clustering_distance_rows = “correlation”,
cluster_cols = F, cluster_rows = T,
show_rownames = T, show_colnames = F
) #������ͼ

pdf(“cibersort_C1C2_heatmap.pdf”,width = 10.5,height = 7)

print(p)

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blue <- “#19307F”
green <- “#238311”
white <- “#FFFFFF”
xiangguan[xiangguan > 0.6] <- 0.6
xiangguan[xiangguan < -0.6] <- -0.6
pheatmap(xiangguan,fontsize=8,
color = colorRampPalette(c(blue,white,green))(10000),

annotation_col = annotation_col,

annotation_colors = ann_colors,

clustering_method = “ward.D2”,
border_color = “grey60”,
clustering_distance_cols = “correlation”,
clustering_distance_rows = “correlation”,
cluster_cols = F, cluster_rows = F,
show_rownames = T, show_colnames = T
) #������ͼ