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TCIA_score
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TCIA_score
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library(GSVA)
library(GSVAdata)
library(GSEABase)
library(org.Hs.eg.db)
library(limma)
library(edgeR)
data(c2BroadSets)
gene.sets <- GeneSetCollection(c2BroadSets)
set =read.csv('/Users/arthurdai/Desktop/GeneSet.csv')
set_new = list(set$Set2, set$Set3, set$Set4,
set$Set6,set$Set7,set$Set8,set$Set9,set$Set10,set$Set11,
set$Set12,set$Set13,set$Set14,set$Set15,set$Set16,
set$Set17,set$Set18,set$Set19,set$Set20,
set$Set21,set$Set24,
set$Set25,set$Set26,set$Set27,set$Set28,set$Set29,
set$Set30,set$Set31,set$Set32,set$Set33,set$Set34,
set$Set35,set$Set36)
set_res = list(set$Set37)
set_gep = list(set$Set_new)
gsva_data <-read.csv('/Users/arthurdai/Desktop/GSE/Pancreas/pancreas_gse_gene.csv', row.names = 1, check.names = F)
gsva_data = as.matrix(gsva_data)
gsva_data = t(gsva_data)
enrichment.scores <- gsva(gsva_data, set_gep, method = "gsva", mx.diff = TRUE, verbose=TRUE)
#brca_e <- enrichment.scores
z <-as.data.frame(scale(t(enrichment.scores)))
colnames(z) <- 'Z'
write.csv(z,'pancreas_gse_gep.csv')