补充材料 supplementary

load("G:/silicosis/geo/GSE104154_scRNA-seq_fibrotic MC_bleomycin/normalized/only_AMs.rds")

markers=FindAllMarkers(subset_data,only.pos = T)
#openxlsx::write.xlsx(markers,file = "G:/silicosis/geo/GSE104154_scRNA-seq_fibrotic MC_bleomycin/normalized/makers_for_AM1_AM2_AM3.xlsx")
markers=openxlsx::read.xlsx("G:/silicosis/geo/GSE104154_scRNA-seq_fibrotic MC_bleomycin/normalized/makers_for_AM1_AM2_AM3.xlsx")
head(markers)

mymarkers=list()
for (eachcluster_markers in unique(markers$cluster)) {
    
  #eachcluster_markers="AM1"
  mymarkers[[paste0(eachcluster_markers)]]=markers[markers$cluster==eachcluster_markers,"gene"] 
} 
head(mymarkers)

fibrosis_gene=openxlsx::read.xlsx("G:/silicosis/fibrosis_geness/harmonizome_gfibrosis.xlsx")
head(fibrosis_gene)
fibrosis_gene=fibrosis_gene$Symbol



#intersect_fibrosis_gene_with_AM
intersected_fibrosis_genes=list()
for (eachcluster_AM in names(mymarkers)) {
    
  intersected_fibrosis_genes[[eachcluster_AM]]=intersect(mymarkers[[eachcluster_AM]],fibrosis_gene)
}

intersected_fibrosis_genes

lapply(intersected_fibrosis_genes,length)


intersected_fibrosis_genes_as_a_vector=as.vector(unlist(intersected_fibrosis_genes))


marker_exp=AverageExpression(subset_data, features = intersected_fibrosis_genes_as_a_vector, return.seurat = TRUE)
DoHeatmap(marker_exp, features = intersected_fibrosis_genes_as_a_vector,
          label=TRUE, group.bar = TRUE, draw.lines = FALSE)

getwd()
pdf('heatmap.pdf',width = 7,height = 14)
p=DoHeatmap(marker_exp, features = intersected_fibrosis_genes_as_a_vector,
            label=TRUE, group.bar = TRUE, draw.lines = FALSE)
print(p)
dev.off()







#supplementary table S7

PF_silicosis_bleo=openxlsx::read.xlsx("G:\\silicosis\\sicosis\\Supplementary Table.xlsx",
                                      sheet = "S7_hPF_Silica_Bleomycin")
head(PF_silicosis_bleo)

library(Hmisc)
library(dplyr)
disease_markers_for_AM3=list()
for (eachdisease in colnames(PF_silicosis_bleo)) {
    
  #eachdisease="Silicosis,.Cluster.AM3"
  disease_markers_for_AM3[[paste0(eachdisease)]]=PF_silicosis_bleo[,eachdisease] %>%
    capitalize()%>% tolower() %>% na.omit() %>% unique()  %>%capitalize()
}
head(disease_markers_for_AM3)

#https://www.jianshu.com/p/58f5429b5402

genes <- Reduce(intersect, list(disease_markers_for_AM3[[1]],
                                disease_markers_for_AM3[[2]],
                                disease_markers_for_AM3[[3]])) %>% capitalize()
length(genes)
getwd()


library(VennDiagram)#https://www.jianshu.com/p/b5a4c40c3a33
venn_list <- list(Human_PF = disease_markers_for_AM3[[1]],
                  Silicosis = disease_markers_for_AM3[[2]],
                  Bleomycin=disease_markers_for_AM3[[3]])

venn.diagram(venn_list, filename = 'venn2_for_humanPF-Silicosi-Bleomycin.png', imagetype = 'png', 
             fill = c('red', 'blue','orange'), alpha = 0.50, cat.col = rep('black', 3), 
             col = 'black', cex = 1.3, fontfamily = 'serif', 
             cat.cex = 1.3, cat.fontfamily = 'serif')

getwd()
#继续以上述4个分组为例，组间交集元素获得
inter <- get.venn.partitions(venn_list)
for (i in 1:nrow(inter)) inter[i,'values'] <- paste(inter[[i,'..values..']], collapse = ', ')
write.table(inter[-c(5, 6)], 'venn4_inter.txt', row.names = FALSE, sep = '\t', quote = FALSE)


for (i in 1:nrow(inter)) inter[i,'values'] <- paste(inter[[i,'..values..']], collapse = ', ')
openxlsx::write.xlsx(inter[-c(5, 6)], 'venn4_inter.xlsx', row.names = FALSE, sep = '\t', quote = FALSE)