design matrix for time point comparision [1 treatment] in time course RNA Seq - EdgeR

Question

[thindmarsmission]

HI! I am trying to analyse Time course data with just one type cell (3 biological replicate ) for each point . I want to compare gene expression based on time point i.e time 1 with time 2 and so on (no treatment comparision at different points, becuase it's one type only).

So what I prepared so far is following and want to know, if I am on right path or not.

pData

minute replicate
r1d0      1         1
r1d1      2         1
r1d2      3         1
r2d0      1         2
r2d1      2         2
r2d2      3         2
r3d0      1         3
r3d1      2         3
r3d2      3         3
r3d3      4         3

dge <- DGEList(counts=exprs(mydata), group=pData(mydata)$minute)
design.mat <- model.matrix(~ 0 + dge$samples$group)
design.mat
colnames(design.mat) <-c("t0","t1","t2","t3","t4","t5","t6","t7","t8")
row.names(design.mat) <- colnames(dge)

# design.mat
#             t0 t1 t2
#r1d0  1  0  0  
#r1d1  0  1  0  
#r1d2  0  0  1
#r2d0  1  0  0 
#r2d1  0  1  0 
#r2d2  0  0  1
#r3d0  1  0  0
#r3d1  0  1  0
#r3d2  0  0  1 

dge = estimateCommonDisp(dge, verbose=TRUE)
dge <- estimateGLMCommonDisp(dge, design.mat)
dge <- estimateGLMTrendedDisp(dge, design.mat, method="power")
dge<- estimateGLMTagwiseDisp(dge,design.mat)
fit.edgeR <- glmFit(dge, design.mat)
contrasts.edgeR <- makeContrasts(t0-t4, levels=design.mat)
lrt.edgeR <- glmLRT(fit.edgeR, contrast=contrasts.edgeR)

I really need to know, if it's correct. what I am doing. Is there anyother tool? which is more better than this.

[WouterDeCoster]

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Answer 1

[Antonio R. Franco]

Why don't you use specialized R packages for time course such as impulseDE2 or maSigPro