设置好gse_id和工作目录，基本全自动

load(".\\table\\CIBERSORT_Results_fromRcode.RData")
load(".\\data\\pdata_paq.RData")
re <- re <- TCGA_TME.results %>% data.frame() %>% select(-c("P.value","Correlation","RMSE"))
group_info <- pdata

library(pheatmap)
k <- apply(re,2,function(x) {sum(x == 0) < nrow(re)/2})

re2 <- as.data.frame(t(re[,k]))
#re[1:10,]

an = data.frame(group = group_info$group,
                row.names = rownames(group_info))
table(group_info$group)

heatmap <- pheatmap(re2,scale = "row",
         show_colnames = F,
         cluster_cols = F,
         annotation_col = an,
         color = colorRampPalette(c("navy", "white", "firebrick3"))(50),
         fontsize = 8)

ggsave(heatmap,filename = ".\\plots\\cibersort_heatmap.pdf",
       width = 89,height = 89,units = "mm")

#--------------------------------------------直方图----------------------------------------------
#可以展示出每个样本的免疫细胞比例
#色板无需修改
library(RColorBrewer)
mypalette <- colorRampPalette(brewer.pal(8,"Set1"))
#宽格式变长格式
dat <- re %>% as.data.frame() %>%
  rownames_to_column("Sample") %>% 
  gather(key = Cell_type,value = Proportion,-Sample)

cibersort_hist <- ggplot(dat,aes(Sample,Proportion,fill = Cell_type)) + 
  geom_bar(stat = "identity") +
  labs(fill = "Cell Type",x = "",y = "Estiamted Proportion") + 
  theme_bw() +
  theme(axis.text.x = element_text(angle = 90,size = 10,vjust = 0.5),
        #axis.ticks.x = element_blank(),
        axis.text = element_text(size = 10),
        legend.position = "right",
        legend.justification = c(1,1),            #不知道是撒意思
        legend.key.size = unit(0.3,"cm"),
        legend.text = element_text(size = 10),
        ) + 
  guides(fill = guide_legend(ncol = 1))+             #把图例放在一列
  scale_y_continuous(expand = c(0.01,0)) +
  scale_fill_manual(values = mypalette(22)) 

ggsave(".\\plots\\cibersort_histplot.pdf",cibersort_hist,width = 120,height = 89,units = "mm")

##------------------------------排序箱线图---------------------------------
a = dat %>% 
  group_by(Cell_type) %>% 
  summarise(m = median(Proportion)) %>% 
  arrange(desc(m)) %>% 
  pull(Cell_type)

dat$Cell_type = factor(dat$Cell_type,levels = a)

ggplot(dat,aes(Cell_type,Proportion,fill = Cell_type)) + 
  geom_boxplot(outlier.shape = 21,color = "black") + 
  theme_bw() + 
  labs(x = "Cell Type", y = "Estimated Proportion") +
  theme(axis.text.x = element_blank(),
        axis.ticks.x = element_blank(),
        legend.position = "bottom") + 
  scale_fill_manual(values = mypalette(22))

##-----------------------------两组对比箱线图------------------------------------
dat$Group = c(rep(group_info$group,22))    #22,是因为有22种免疫细胞
dat %>% dim()
library(ggpubr)
cibersort_compare_boxplot <- ggplot(dat,aes(Cell_type,Proportion,fill = Group)) + 
  geom_boxplot(outlier.shape = 21,color = "black") + 
  theme_bw() + 
  
  labs(x = "Cell Type", y = "Estimated Proportion") +
  theme(legend.position = "top") + 
  theme(axis.text.x = element_text(angle=80,vjust = 0.5))+
  scale_fill_manual(values = mypalette(22)[c(6,1)])+ stat_compare_means(aes(group =  Group),
                                                                        label = "p.signif",
                                                                        method = "wilcox.test",
                                                                        hide.ns = T)
ggsave("cibersort_compare_boxplot.pdf",cibersort_compare_boxplot,width = 17.5,height = 12,units = "cm")