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Old 08-17-2014, 11:45 PM   #16
Location: USA

Join Date: May 2014
Posts: 24

Dear mikep and mbblack

Thank you so much for your comments.
I have one more quick question. I tried to analyze my data to find DEG in two condition. I have used edgeR, DESeq, DESeq2, cuffdiff or just simple wilconxon rank sum test etc.
However, I could not find any DEG with adjusted p value in any of these methods..

There are two hypothesis.
1) Hypothesis 1

Maybe, our experimental design is wrong so we could not detect any significant gene at all.. That is the reason we could not identify any DEG gene.. (End of story..) we could not do anything !!!
( I hope it is not !! cause there should be some genes responsing our drug)

2) Hypothesis 2

In some reason(small sample, so little statistical power), we could not find statistically significant DEG genes with adjusted p-value. (Still we could find some DEGs with p value) even though there exist DEG genes responsing the drug.


In this case, what option I can choose?
I could not just throw away our data. I would like to find meaningful output........

So, I am thinking that (based on your suggestion)

Just use the pvalue to detect DEG genes and do any additional analysis with these DEG gene based on pvalue.. and then if we filter some more meaningful DEG among previously detected DEG genes,we can validate with experimental validation. (qPCR etc I am not sure how it would be feasible because of lack of money! ) ...
Or is there any other way we can claim our result without experimental validation??? Any suggestion??

Or Experiemnental validation is the only way I can do??
younko is offline   Reply With Quote