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Quantitative RT-PCR statistics help - (Oct/07/2013 )



I have probably a pretty basic question about analysing RT-qPCR data.  I've never had to do this type of experiment before, so I am totally out of my depth and getting very very confused and probably completely over-thinking things.


Basically, all I want to do is compare the expression of one gene (fold change or ratio) across two types of tissue.  I've done all my standard curves, my PCRs are properly efficient, producing only one product - so that's all good :)  I've run my PCRs have have Ct values for each of my samples - three samples from one tissue type, three from the other.  Everything was run in triplicate and my reference gene is GAPDH (expression of which was not altered between the two tissues in a microarray).


So, what I'm confused with is what to do with the Ct values.  I've tried my hand at going through the comparative Ct method and the Pfaffl method.  The way I'm doing it, I just get one ratio at the end.  How am I suppose to perform statistical analysis on the one ratio?  Am I doing this wrong?  I have no idea what I'm doing!


Thanks for reading x


When you state you have just have one ratio, do you mean one ratio per tissue type or one ratio between the two tissue type. You should have mutiple cDNAs from each of the tissue types as your biological replicates - 3 of tissue A and 3 of tissue B. Then you can run RT-qPCR in triplicate (technical replicates) for each of these cDNAs, and compare. 


Also, you produced a standard curve for both gene x and GAPDH. Did this standard curve have a broad range with multiple points (i.e. 10^9 cp, 10^8 cp,....10^1 cp)? You can calculate cp number from the standard curve for each sample then normalize gene x cp to GAPDH cp. Then compare replicates between both tissue types.