R/getIPS.R

In Liulab/PD1highCD8Tscore: Quantify PD-1hiCD8+ T cells in tumor environment

getIPS <-
function(gene_expression,IPSG=IPSG){
#expression values (i.e. log2(TPM+1)) for each sample in the other columns
gene_expression<-as.data.frame(log2(gene_expression+1))
sample_names<-colnames(gene_expression)
## Read IPS genes and corresponding weights from tab-delimited text file "IPS_genes.txt"
# For different 

unique_ips_genes<-as.vector(unique(IPSG$NAME))

IPS<-NULL
MHC<-NULL
CP<-NULL
EC<-NULL
SC<-NULL
AZ<-NULL

# Gene names in expression file
GVEC<-row.names(gene_expression)
# Genes names in IPS genes file
VEC<-as.vector(IPSG$GENE)
# Match IPS genes with genes in expression file
ind<-which(is.na(match(VEC,GVEC)))
# List genes missing or differently named
MISSING_GENES<-VEC[ind]
dat<-IPSG[ind,]
if (length(MISSING_GENES)>0) {
cat("differently named or missing genes: ",MISSING_GENES,"\n")
}
for (x in 1:length(ind)) {
  print(IPSG[ind,])
}

for (i in 1:length(sample_names)) {
GE<-gene_expression[[i]]
mGE<-mean(GE)
sGE<-sd(GE)
Z1<-(gene_expression[as.vector(IPSG$GENE),i]-mGE)/sGE
W1<-IPSG$WEIGHT
WEIGHT<-NULL
MIG<-NULL
k<-1
for (gen in unique_ips_genes) {
MIG[k]<- mean(Z1[which (as.vector(IPSG$NAME)==gen)],na.rm=TRUE)
WEIGHT[k]<- mean(W1[which (as.vector(IPSG$NAME)==gen)])
k<-k+1
}
WG<-MIG*WEIGHT
MHC[i]<-mean(WG[1:10])
CP[i]<-mean(WG[11:20])
EC[i]<-mean(WG[21:24])
SC[i]<-mean(WG[25:26])
AZ[i]<-sum(MHC[i],CP[i],EC[i],SC[i])
IPS[i]<-ipsmap(AZ[i])}
DF<-data.frame(SAMPLE=sample_names,IPS=IPS)
return(DF)
}