Hello,
I have a time series RNA Seq data (time point 0 -> 48hours with step = 8hours). There are no replicates for each time point and also there is no control to check fold change against. But, somehow we want to be able to find genes that might have a differential expression over time point and use them for further analysis in GO enrichment and motif finding. Is there any tool that can be used or any paper where a similar analysis been done.
Appreciate your suggestions. Thanks
PS: I could only think of finding the difference between max - min (normalized gene counts from) as fold - change for every gene. But I am not sure if this is correct.
-RT
1 answer
Providing you're not interested in "novel" discovery - Then Alignment -> Read counting -> DESeq2 is probably the best way to go.
Alignment can be done using a variety of tools, specifically Tophat or RNAStar would be good places to start.
Read counting try HTSeq_Count or maybe feature counts (R wrapper package)
Differential expression can be done with DESeq2 in R. Check out this particular example https://support.bioconductor.org/p/63201/ Which shows a typical model for a time series experiment.
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