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Old 10-03-2016, 07:58 AM   #1
Location: Japan

Join Date: Apr 2014
Posts: 40
Default Time Course RNA-Seq


We just finished the QC for the total reads obtain from a Time Course RNA-Seq experiment (Illumina HiSeq2000), and are satisfied with the quality.
Now we have started the Differential Expression Gene analysis, and the strategy proposed by our bioinformatican was the following:
Calculating DEG for every condition compared with the initial one, so we will have at the end 5 comparisons. DEG for each gene will show a certain p-value in each case, so we would count as statistically significant those genes with p-value<0.05 in all 5 comparisons.

Do you think this is a right approach?

Thanks in advance for your comments and advices.
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Old 10-03-2016, 02:10 PM   #2
Devon Ryan
Location: Freiburg, Germany

Join Date: Jul 2011
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I hope he/she proposed that as only a quick and easy first go while a more useful analysis was being performed...

If your goal is to find "all genes that change with time" (this is at least biologically interesting), then tell your bioinformatician to "fit the samples with a model of the form '~time', with 'time' as a factor, and then perform an LRT with '~1' as the reduced model".

Analysing time-course data is a bit of an art in itself if what I wrote above isn't the question you're interested in answering. At that point, you're best of doing a bit of clustering and trying to determine the proper course of action from how the samples cluster together.
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Old 10-06-2016, 06:41 AM   #3
Location: Germany/Netherlands

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I'd make DE all vs all, then sort out the statistically significant ones (no matter where they are significant) and do clustering on these (as suggested), to see which patterns are in there.

I don't have any experience with time course data myself, but this is probably what I'm going to do with my current time course (running the clustering on the whole dataset though....right now; might sort the DE ones out afterwards...or maybe I'll change that again the other way round, not sure yet).
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Old 10-11-2016, 11:00 PM   #4
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Location: Sydney, Australia

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You should provide more guidance to the bioinformatician collaborating with you. What is your biological hypothesis? Why did you do the experiment? There must have been particular reasons for choosing the timepoints you chose, which you need to inform the bioinformatician about.
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