Extraction_rows

 pc <- c(65,51,29,75,50,1,70,47,37,36,45,44,57,66,60,71,40,39,34,21,27,17,43,19,49,88,58,55,30,18,64,74,72,63,26,22,28,52,35,23,68,41,62,24)#define the columns that you are interested in


 t1 <- y[obj,pc]#making group1
 t2 <- y[obj,-pc]#making group2

 t <- cbind(t1,t2)

#define the comparison
 c <- c(rep(1,44),rep(0,52))
 d <- c(rep(0,44),rep(1,52))
 design = cbind(Cell_A = c, Cell_B = d)
 contrastsMatrix = makeContrasts("Cell_B-Cell_A",levels = design)# We want to compare A vs. B, A vs. C and B vs. C

#comparison of the levels of the genes between group 1 and 2

 library(limma)
 fit = lmFit(t,design=design)
 fit2 = contrasts.fit(fit, contrasts = contrastsMatrix)
 out = eBayes(fit2)
 p.value = out$p.value #to put p.values for indevisual genes into the vector, p.value
 q.value = apply(p.value, MARGIN=2, p.adjust, method="BH")
 ranking = apply(p.value, MARGIN=2, rank)#to put the ranking for indevisual genes in term of p.value into the vector, ranking

#making the table for the results
 tmp = cbind(t, p.value, q.value, ranking)

#making the heatmap for top 60 differentially expressed genes

 ob = rank(tmp[,ncol(tmp)-2])< 65
 tmp3 = tmp[ob,]

 library(gplots)

 z = tmp[,1:96]
 heatmap.2(as.matrix(z), col=greenred(75), scale="row", key=T, keysize=1.5,density.info="none", trace="none",cexCol=0.9, cexRow=0.5)

 z = tmp3[,1:96]
 heatmap.2(as.matrix(z), col=greenred(75), scale="row", key=T, keysize=1.5,density.info="none", trace="none",cexCol=0.9, cexRow=0.5)
 write.table(tmp,file="output.txt",sep="\t")