Fold change graph - (Feb/20/2012 )
I am performing qPCR data analysis by using delta delta ct method in Excel.
I have two group samples (Control and Treated) and comparing them for the relative changes in gene expression level . In order to do statistical analysis (Wilcoxon Test) I used delta delta ct values and obtained p-values and standard error mean of these delta delta ct values in treated group.
If I would like to show the graphs for relative fold changes of genes in treated group vs control group I also need to provide standard error mean.
Now my question is:should I need to use standard error mean of delta delta ct statistical calculation? or standard error mean of average fold change (2-ΔΔCt) of the genes in treated group?
Looking for your kind response.
Unfortunatelly I do not have an answer to your question, but I have a problem and because you also use 2 groups and compare them using 2-ΔΔCT method, maybe you could help me, please ?
I have 2 groups as treatment and home-cage control. I am looking for the effects of the treatment on the expression levels of some genes, for example CRH. So I have to show if there is a statistically significant differences between treatment and control groups considering this gene. I have used GAPDH as a house-keeping gene. When calculating 2-ΔΔCT values of the groups, Ct values of individuals first normalized according to GAPDH, then to the home cage control group ( I used control group as a calibrator). For the treatment group there is no problem, the values I obtained by 2-ΔΔCT method can be statistically comparable. However control groups' 2-ΔΔCT values corresponds to1 (It has to be 1, because the control group is also the calibrator when calculating ΔΔCT, ΔCT of the group substracted from ΔCT of the calibrator, which is also the same value).
How did you compare these 2 groups statistically? If the control groups values all correspond to 1, how would you calculate statististical differences and p value?
Sorry for the unrelevant comment and thank you very much in advance for your answer.