Hi,
I have a time course experiment with vehicle, drug-4h, and drug-24h and its colData look like this:
| condition | time |
| ------------:| -----: |
| control | 0h |
| control | 0h |
| control | 0h |
| control | 0h |
| treat | 4h |
| treat | 4h |
| treat | 4h |
| treat | 4h |
| treat | 24h |
| treat | 24h |
| treat | 24h |
| treat | 24h |
I was wondering if it is suitable to use
ddsTC <- DESeqDataSet(data, ~ condition + time + condition:time)
ddsTC <- DESeq(ddsTC, test="LRT", reduced = ~ condition + time)
in this case? I noticed that the example provided in 'RNA-seq workflow' tutorial is balanced (e.g control 0h/4h/24h and treat 0h/4h/24h), so I am not sure if I could use time course analysis in my case or I could just do three normal comparisons, e.g vehvsdrug4h, vehvsdrug24h and drug4hvsdrug24h?
Thanks in advance!
Kun
Understand~ thanks!
Kun
Hi, Michael
Sorry for bothering again, I was wondering what's the best way to analysis time course experiment with two drugs? For example, Veh, drug1-4h, drug1-24h, drug2-4h and drug2-24h? Thanks!
Best,
Kun
I don't have a best way to analyze this, it depends on your research questions and assumptions... sorry I have to restrict my time on the support site to focus on DESeq2-specific software questions, as you can imagine there are an unlimited number of statistical analysis questions that someone might have for an RNA-seq dataset.
Understand~ but still thanks for your reply and time!
Best,
Kun