#MCA Macrophage
Macro <-c("Chil3","Ccl9","S100a4","Lyz2","Thbs1","Ms4a4c","F10","Ly6c2","Gda","Lgals3")
#MCA Kupffer_cell
KC <- c("Vsig4","Cd5l","Fcna","Cfp","C1qc","Clec4f","Ctsc","Adgre1","Fabp7","C1qa")
#MCA Endothelial_cell
np <- c("Cxcl10","Clec4g","Igfbp7","Adamts1","Plpp3","Iigp1","Kdr","Nrp1","Cyp4b1","Socs3")
#MCA DC
DC <- c("Cst3","Ccr7","H2-Eb1","Ccl22","H2-Aa","Naaa","Gm2a","H2-Ab1","Ppt1","Cytip")
#MCA T_cell
T1 <- c("Gzma","Gzmb","Ccl5","Xcl1","Cd7","Gzmc","Il2rb","Nkg7","Klrb1b","Cd3g")
T2 <- c("Trbc2","Trac","Icos","Satb1","Isy1","Ms4a4b","Cd3d","Trbc1","Sh2d2a","Cd28")
#MCA B_cell
B1 <- c("Bank1", "Bcl11a", "Cd19", "Cd22", "Cd37", "Cd74", "Cd79a", "Cd79b", "Cxcr4", "Ebf1", "Fcer2a", "Fcmr", "Fcrla")
PB <- c("Creld2", "Crip1", "Derl3", "Dnajc3", "Eaf2", "Edem1", "Edem2", "Fam46c", "Glipr1", "Gm43291", "H13", "Herpud1", "Hsp90b1", "Igha", "Igkc", "Iglc2", "Jchain")
#MCA Hepatocyte
Hepa <- c("Alb","Apoa1","Fgb","Gc","Ahsg","Kng1","Mup3","Car3","Gsta3","Hpd","Ass1","Mat1a","Bhmt","Fabp1","Aldob","Wfdc21")
#Cholangiocyte
chol <- c("Alcam", "Ambp", "Ankrd1", "Anxa5", "Atp1b1", "Bicc1", "Ces1d", "Cldn3", "Cldn7", "Clu", "Cp", "Cyr61", "Cystm1", "Dbi", "Ddit4l", "Dsg2")
#HSC
hscc <- c("Angptl6", "Bgn", "C3", "C4b", "Col14a1", "Col1a1", "Col1a2", "Col3a1", "Colec11", "Cxcl12", "Cygb", "Dcn", "Dpt", "Ecm1", "Efemp1", "Gsn", "Ifitm1", "Igfbp5", "Igfbp6")
#合并
markers <- c(KC,PB,T1,T2,DC,np,B1,chol,Macro,hscc,Hepa)
● 按照上述代码确定markers,用markers和Seurat_cluster绘制点图(根据簇注释细胞类型)
#点图
DotPlot(scRNA, features = unique(markers),group.by = "seurat_clusters")+RotatedAxis()+
scale_x_discrete("")+scale_y_discrete("")
ggsave("celltype_marker_dot.pdf",width = 9.5,height = 6)
● 绘制图表如下(例将cluster6,9,10注释为KC细胞/将cluster13注释为PB细胞)
new.cluster.ids <- c("Endothelial_cell","T_cell",
"T_cell","Endothelial_cell","Macrophage","B_cell",
"Kupffer_cell","B_cell","DC","Kupffer_cell",
"Kupffer_cell","Cholangiocyte","Hepatocyte",
"Plasma_B_cell","Endothelial_cell",
"HSC")
scRNA@meta.data$celltype<- scRNA@meta.data$seurat_clusters
levels(scRNA@meta.data$celltype) <- new.cluster.ids#将celltype确定
● 此时celltype已经确定了,选取每个细胞的特异性高表达基因
#点图
DotPlot(scRNA, features = unique(markers),group.by = "celltype")+RotatedAxis()+
scale_x_discrete("")+scale_y_discrete("")
ggsave("celltype_marker_dot111.pdf",width = 9.5,height = 6)
#特异性高表达基因,与markers不同
marker<-c("Clec4g","Nrp1","Ccl5","Nkg7","S100a4","Lyz2","Cd79a", "Cd79b","Cd5l","C1qa","Cst3","Gm2a","Alcam", "Ambp","Mup3","Car3","Glipr1", "Fam46c","Col14a1", "Col1a1")