pre-process.R

library(Seurat)
library(R.utils)
# example_data is Seurat object after log-normalization having 199 mouse testis spermatocyte cells
mouse_Testis199<- readRDS('R/example_data.rds')
mouse_Testis199<- mouse_Testis199[['RNA']]@data
geneinfo<- readRDS('R/geneinfo.rds')

# revising gene symbols
genename<- rownames(mouse_Testis199)
genename1<- genename[genename %in% geneinfo$Symbol]
genename2<- genename[!genename %in% geneinfo$Symbol]
genename3<- genename2[genename2 %in% geneinfo$Synonyms]
genename4<- rep('NA',length(genename3))
for (i in 1:length(genename3)) {
  d1<- geneinfo[geneinfo$Synonyms == genename3[i],]$Symbol
  if(length(d1) == 1){
    genename4[i]<- d1
  }
}
genename3<- c(genename1,genename3)
genename4<- c(genename1,genename4)
genedata<- data.frame(raw_name = genename3,new_name = genename4,stringsAsFactors = F)
genedata<- genedata[!genedata$new_name == 'NA',]
genedata1<- as.data.frame(table(genedata$new_name),stringsAsFactors = F)
genedata1<- genedata1[genedata1$Freq == 1,]
genedata<- genedata[genedata$new_name %in% genedata1$Var1,]
mouse_Testis199<- mouse_Testis199[genedata$raw_name,]
all(rownames(mouse_Testis199) == genedata$raw_name)
rownames(mouse_Testis199)<- genedata$new_name
all(rownames(mouse_Testis199) == genedata$new_name)
all(rownames(mouse_Testis199) %in% geneinfo$Symbol)

# for log-normalization, please execute the following command
# mouse_Testis199<- CreateSeuratObject(counts = mouse_Testis199)
# mouse_Testis199<- NormalizeData(object = mouse_Testis199)
# mouse_Testis199<- mouse_Testis199[['RNA']]@data

mouse_Testis199<- as.matrix(mouse_Testis199)
write.csv(mouse_Testis199,file = 'test/mouse/mouse_Testis199_data.csv')
gzip('test/mouse/mouse_Testis199_data.csv','test/mouse/mouse_Testis199_data.gz')

# mouse_Testis199_data.csv or mouse_Testis199_data.gz can be used for running scDeepSort