Dear RG comunity,
I am analyzing my qPCR data of male and female, treated and non treated groups. Considering there are reasons to assume treatment may diffrently affect expression of genes of interest according to sex, two-way ANOVA seems appropriate (assumptions checked).
What I ask for help is the normalization process in the 2-ΔΔCt calculation, for which average ΔCt values of a reference/control group are important to calculate expression in the treated group. If I normalize values separated to sex (e.g. use ΔCt values of untreated males to calculate 2-ΔΔCt for treated males and do in the same way with females), would I still be able to compare sex or treatment x sex effects of a 2-way ANOVA?
Best regards,
Rodrigo
You have ΔCt values. This is your response. It is reasonable to assume that ΔCt values are normal distributed.
Your experiment has two factors (sex and treatment). Hence, you should use a conventional (two-) factorial model including the sex:treatment interaction to analyze the differential effect of the treatment between the sexes.
There is no need to specify any "control" or to "normalize" against anything.
Particularly, don't calculate 2^-ΔΔCt and don't use such values for your analysis - they can not assumed normal distributed, and they should not be analyzed with conventional statistical models (that assume the response being normal distributed).
Hi, I agree with Jochen Wilhelm . In addition, if you want to facilitate your comparisons and discussion later, you can use one group to relativize your data (e.g., The untreated male group).
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