require(edgeR)
rnaseqMatrix0= read.table("transcript_count_matrix.csv",header=T,sep=",")

#,1:KO_0h_replicate_I,2:KO_0h_replicate_II,3:KO_2h_replicate_I,KO_2h_replicate_II,5:KO_6h_replicate_I,KO_6h_replicate_II,7:KO_IFN-gamma_replicate_I,KO_IFN-gamma_replicate_II,9:KO_IL4_replicate_I,KO_IL4_replicate_II,11:WT_0h_replicate_I,WT_0h_replicate_II_,13:WT_2h_replicate_I,WT_2h_replicate_II,15:WT_6h_replicate_I,WT_6h_replicate_II,17:WT_IFN-gamma_replicate_I,WT_IFN-gamma_replicate_II,19:WT_IL4_replicate_I,WT_IL4_replicate_II
col_ordering = c(21,22,5,6)#0h
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
#r <- rownames(topTags(et)$table)
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#detags <- rownames(exp_study)[as.logical(de)]
#plotSmear(et, de.tags=detags)
#abline(h = c(-1, 1), col = "blue")
#write.table(tTags, file="edgeRtranscripts-0h.csv")
write.table(x, file="edgeRtranscriptsExpr-0h.csv")

col_ordering = c(23,24,7,8)#2h
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-2h.csv")
write.table(x, file="edgeRtranscriptsExpr-2h.csv")

col_ordering = c(25,26,9,10)#6h
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-6h.csv")
write.table(x, file="edgeRtranscriptsExpr-6h.csv")

col_ordering = c(27,28,11,12)#IFN
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-IFN.csv")
write.table(x, file="edgeRtranscriptsExpr-IFN.csv")

col_ordering = c(29,30,13,14)#IL4
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-IL4.csv")
write.table(x, file="edgeRtranscriptsExpr-IL4.csv")
colnames(rnaseqMatrix)
#awk -f addGeneToEdger.awk all_pairs_edger.txt
#edgeRtranscriptsExpr-0h.csv

col_ordering = c(31,33,15,16)#0h
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
#r <- rownames(topTags(et)$table)
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-0h-RNAseq.csv")
write.table(x, file="edgeRtranscriptsExpr-0h-RNAseq.csv")

col_ordering = c(35,36,1,2)#2h
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-2h-RNAseq.csv")
write.table(x, file="edgeRtranscriptsExpr-2h-RNAseq.csv")

col_ordering = c(37,38,19,20)#6h
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-6h-RNAseq.csv")
write.table(x, file="edgeRtranscriptsExpr-6h-RNAseq.csv")

col_ordering = c(39,40,3,4)#IFN
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-IFN-RNAseq.csv")
write.table(x, file="edgeRtranscriptsExpr-IFN-RNAseq.csv")

col_ordering = c(32,34,17,18)#IL4
rnaseqMatrix =rnaseqMatrix0[,col_ordering];rnaseqMatrix = rnaseqMatrix[rowSums(rnaseqMatrix)>=2,];conditions = factor(c("WT","WT","KO","KO"));
exp_study = DGEList(counts=rnaseqMatrix, group=conditions);exp_study = calcNormFactors(exp_study);exp_study = estimateCommonDisp(exp_study);exp_study = estimateTagwiseDisp(exp_study);et = exactTest(exp_study)
tTags = topTags(et,n=NULL,adjust.method = "fdr")
r <- rownames(tTags)
c=cpm(exp_study)[r, order(exp_study$samples$group)]
x=cbind(as.data.frame(tTags),c)
summary(de <- decideTestsDGE(et, p=0.05))
#write.table(tTags, file="edgeRtranscripts-IL4-RNAseq.csv")
write.table(x, file="edgeRtranscriptsExpr-IL4-RNAseq.csv")
colnames(rnaseqMatrix)