颜色色彩选取火山图vocanoxiwen

这个RStudio插件，是最好用的图形颜色拾取器之一

手把手教你做单细胞测序数据分析|6组间差异分析

 

.libPaths(c("/home/data/refdir/Rlib/",  "/home/data/t040413/R/x86_64-pc-linux-gnu-library/4.2", "/usr/local/lib/R/library"))

library(Seurat)

getwd()
setwd("/home/data/t040413/xiwen/")
pbmc=readRDS("./immune.combined.rds")

head([email protected])

table(pbmc$seurat_clusters)
'''
#table(pbmc$stim)
table(pbmc$celltype.stim)
pbmc$group=pbmc$stim
pbmc$orig.celltype=pbmc$celltype
pbmc$celltype.group <- as.factor(paste(pbmc$celltype, pbmc$group, sep = "_"))
pbmc$celltype <- pbmc$celltype.group
Idents(pbmc) <- "celltype.group"
'''
pbmc$celltype.group=pbmc$celltype.stim
pbmc$celltype=pbmc$seurat_clusters
Idents(pbmc)=pbmc$celltype.group

cellfordeg<-levels(pbmc$celltype)

data_forplot=data.frame()

for(i in 1:length(cellfordeg)){ #
  CELLDEG <- FindMarkers(pbmc, ident.1 = paste0(cellfordeg[i],"_PT"), ident.2 = paste0(cellfordeg[i],"_sham"), verbose = FALSE)
  CELLDEG$gene=rownames(CELLDEG)
  CELLDEG$cluster=cellfordeg[i]
  write.csv(CELLDEG,paste0(cellfordeg[i],"PT_VS_Sham.CSV"))
  data_forplot=rbind(CELLDEG,data_forplot)
  

}
head(data_forplot)
table(data_forplot$cluster)

getwd()
save(data_forplot,file="data_forplot.rds")
load("/home/data/t040413/xiwen/data_forplot.rds")
#request 2===========================================================----------------------------------------------------------
.libPaths(c( "/home/data/t040413/R/x86_64-pc-linux-gnu-library/4.2","/home/data/t040413/R/yll/usr/local/lib/R/site-library",  "/home/data/refdir/Rlib/", "/usr/local/lib/R/library"))
library(Seurat)

library(scRNAtoolVis)
library(colourpicker)


markers_for_all_3groups=data_forplot

head(markers_for_all_3groups)
getwd()


# plot


jjVolcano(diffData = markers_for_all_3groups, 
          legend.position = c(0.93, 0.99), 
          topGeneN=2,#top genes to be labeled in plot, default 5.
          cluster.order=seq(0,23,1),
          pSize=0.4,
          tile.col = c("#EE3B3B", "#FF7F00", "#CD6600", "#8B2323", "#DEB887", "#76EEC6", 
                     "#F0FFFF", "#008B8B", "#FFB90F", "#F5F5DC", "#1F1F1F", "#66CD00", 
                     "#0000FF", "#97FFFF", "#528B8B", "#9400D3", "#EE1289", "#00BFFF", 
                     "#00FF00", "#191970", "#FFFF00", "#4A708B", "#00FF7F", "#8B8B00", 
                     "#FF1493", "#FFA500", "#8B4513")) 


ggsave("./1_differential_genes_indifferent_clusters.pdf",width = 20,height = 7,dpi = 900,limitsize = FALSE)



jjVolcano(diffData = markers_for_all_3groups, 
          legend.position = c(0.93, 0.99), 
          topGeneN=0,#top genes to be labeled in plot, default 5.
          cluster.order=seq(0,23,1),
          pSize=0.4,
          tile.col = c("#EE3B3B", "#FF7F00", "#CD6600", "#8B2323", "#DEB887", "#76EEC6", 
                       "#F0FFFF", "#008B8B", "#FFB90F", "#F5F5DC", "#1F1F1F", "#66CD00", 
                       "#0000FF", "#97FFFF", "#528B8B", "#9400D3", "#EE1289", "#00BFFF", 
                       "#00FF00", "#191970", "#FFFF00", "#4A708B", "#00FF7F", "#8B8B00", 
                       "#FF1493", "#FFA500", "#8B4513")) 


ggsave("./1_differential_genes_indifferent_clusters_nogenes.pdf",width = 20,height = 7,dpi = 900,limitsize = FALSE)



jjVolcano(diffData = markers_for_all_3groups, 
          legend.position = c(0.93, 0.99), 
          topGeneN=0,#top genes to be labeled in plot, default 5.
          cluster.order=seq(0,23,1),
          pSize=0.4,
          tile.col = c("#EE3B3B", "#FF7F00", "#CD6600", "#8B2323", "#DEB887", "#76EEC6", 
                       "#F0FFFF", "#008B8B", "#FFB90F", "#F5F5DC", "#1F1F1F", "#66CD00", 
                       "#0000FF", "#97FFFF", "#528B8B", "#9400D3", "#EE1289", "#00BFFF", 
                       "#00FF00", "#191970", "#FFFF00", "#4A708B", "#00FF7F", "#8B8B00", 
                       "#FF1493", "#FFA500", "#8B4513")) 


ggsave("./1_differential_genes_indifferent_clusters_nogenes_.pdf",width = 14,height = 7,limitsize = FALSE,dpi = 900)


jjVolcano(diffData = markers_for_all_3groups, 
          legend.position = c(0.93, 0.99), 
          topGeneN=0,#top genes to be labeled in plot, default 5.
          cluster.order=seq(0,23,1),
          pSize=0.4,
          tile.col = c("#EE3B3B", "#FF7F00", "#CD6600", "#8B2323", "#DEB887", "#76EEC6", 
                       "#F0FFFF", "#008B8B", "#FFB90F", "#F5F5DC", "#1F1F1F", "#66CD00", 
                       "#0000FF", "#97FFFF", "#528B8B", "#9400D3", "#EE1289", "#00BFFF", 
                       "#00FF00", "#191970", "#FFFF00", "#4A708B", "#00FF7F", "#8B8B00", 
                       "#FF1493", "#FFA500", "#8B4513")) 


ggsave("./1_differential_genes_indifferent_clusters_nogenes___.pdf",width = 10,height = 7,limitsize = FALSE,dpi = 900)




#############################################3
head(markers_for_all_3groups)
openxlsx::write.xlsx(markers_for_all_3groups,file = "./differential_genes_between_three_groups.xlsx")



# change aes color type
jjVolcano(diffData = markers_for_all_3groups,
          log2FC.cutoff = 0.5,
          col.type = "adjustP",
          topGeneN = 3)

# supply own genes
mygene <- c('PD-1', 'TIM3', 'TIGHT', 'CTLA-4', 'CD244', 'CD39', 'CD73')

jjVolcano(diffData = markers_for_all_3groups,legend.position = c(0.9,0.99),
          myMarkers = mygene)