I am facing the troubles with relative QPCR data evaluation. I have two groups - patients vs. healthy controls. Usually I use 2^-dCt method and compare by Student t-test or Mann-Whitney test the values between the two groups. I cannot use ddCt (or 2^-ddCt) method because I do not have a calibrator (treated vs. untreated sample or subject before treatment and after treatment). Nevertheless, the 2^-dCt method is OK only when the efficiencies of GOI and HK are equal. In my current project, the efficiencies are different and there is no possibility to design other primers to change E because the amplified locus is extremely variable (no space to shift primers). Because of not having calibrator I cannot use Pfaffl equation number 1 published in Nucleic Acids Research in 2001 that deals with different PCR efficiencies in GOI and HK. Any suggestions how to analyze my data?
I saw some people are doing sort of "trick" in case they do not have a calibrator - they simply choose one of the samples and they compare all other tested samples to this one. I understand that in case we "only" need to know whether the expression of GOI differs between the two groups and how much (where is less and where is more and need to compare), maybe this could make its job. But still, somehow this does not feel right.
Hopefully I explained it understandable. :-) Thank you for any help.
How did you calculate your primer efficiencies? If you included a standard curve as a control, then use that adjust your data with the Pfaffl correction.
The best approach is to clone your gene of interest into a plasmid, linearize the plasmid, create a dilution series, and use that as your reference.
You can't rush quality.
Also, it's completely valid to use one sample as a reference to compare all of the rest. It's a "relative expression" experiment as opposed to an "absolute expression" experiment.
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