I would like to address an important question regarding a GEO a time series dataset, GSE21059. I used limma package for preprocessing.
In detail, I'm asking about the specific step considering contrasts I would use. Part of my relevant code (after preprocessing/normalization etc):
grouping <- paste0(final$targets$Sample.and.Data.Relationship.Format, ".", final$targets$time)
head(grouping)  irradiated.0.5h irradiated.0.5h irradiated.0.5h irradiated.0.5h bystander.0.5h bystander.0.5h 18 Levels: bystander.0.5h bystander.1.0h bystander.2.0h bystander.24.0h bystander.4.0h ... irradiated.6.0h batch <- factor(final$targets$Batch) # where batch the 4 different biological replicates
> head(batch)  1 2 3 4 1 2 Levels: 1 2 3 4 design <- model.matrix(~0 + grouping + batch) colnames(design)  "groupingbystander.0.5h" "groupingbystander.1.0h" "groupingbystander.2.0h" "groupingbystander.24.0h"  "groupingbystander.4.0h" "groupingbystander.6.0h" "groupingcontrol.0.5h" "groupingcontrol.1.0h"  "groupingcontrol.2.0h" "groupingcontrol.24.0h" "groupingcontrol.4.0h" "groupingcontrol.6.0h"  "groupingirradiated.0.5h" "groupingirradiated.1.0h" "groupingirradiated.2.0h" "groupingirradiated.24.0h"  "groupingirradiated.4.0h" "groupingirradiated.6.0h" "batch2" "batch3"  "batch4"
Also, it is important to mention that there are control samples (groups) also for each time point and not "universal"
My main goal, is to identify any putative DE genes, that could discriminates/separate Bystander samples from irradiated ones, totally and not only for example in a specific time point. Thus, i thought a naive setting of contrasts.fit in the following lines:
con <- makeContrasts(total comparison =((groupingirradiated.0.5h + groupingirradiated.1.0h + groupingirradiated.2.0h + groupingirradiated.4.0h + groupingirradiated.6.0h + groupingirradiated.24.0h)/6 - (groupingbystander.0.5h + groupingbystander.1.0h + groupingbystander.2.0h + groupingbystander.4.0h + groupingbystander.6.0h + groupingbystander.24.0h)/6), levels=design).......
With this approach, i ended in 20 DE genes with an FDR cutoff < 0.05: which, despite the relatively small number, are implicated in interesting biological processes relative to our studied phenomenon. However, in a following heatmap-including only the bystander and irradiated samples--, there was not a clear separation.
Thus, in your opinion:
1) Could be an "improved" formulation of my above contrasts fit, in order to identify any DE genes above all the time points that discriminate directly bystander and irradiated samples ? Or my notion is incorrect, based on the fact of different times points, and i should follow a different approach
2) Even if my methodology above is vital, the above identified genes could still "be valid" --except their biological relevance", but perhaps try a different approach before heatmap construction? In other words, for instance compute the average of each one of these genes in the batches for each condition, and then perform the heatmap ? In the context, of perhaps different time points in the heatmap and/or batches affect the clustering of these genes?
Thank you in advance,