I suggest doing a standard 2x2 factorial analysis based on the dCt values. With the standard coding you will get the main effect of diet type (effect of the diet in WT animals) and the main effect of genotype (effect of the mutation in normal diet) and - and this is the scientifically most interesting part! - the genotype:diet interaction, which tells you if the effect of the diet depends on the genotype (if the mutation has a "diet-specific" effect).

I suggest doing a standard 2x2 factorial analysis based on the dCt values. With the standard coding you will get the main effect of diet type (effect of the diet in WT animals) and the main effect of genotype (effect of the mutation in normal diet) and - and this is the scientifically most interesting part! - the genotype:diet interaction, which tells you if the effect of the diet depends on the genotype (if the mutation has a "diet-specific" effect).

We check for diet*drug interaction and analyze our data similar way. To me, your workflow sounds correct.

Hi Carrie,

Your normalization sounds correct to me.

1. Is the WT for the normal group my control data? Can I compare all other groups to that, within the same gene expression data?

Yes you can. Usually, the wild type or the normal group used as a contol for normalization.

2. Am I able to compare the Normal-TG to Normal-WT (same diet) to see how gene expression varies within the same diet group?

Yes, you can

3. Is it normal to have my Normal-WT as a value of 1 when I arrive at final FC data.

It is usually normal to have an average ddct value of around 1 for the control group unless you have huge variations.

Thanks!

Yasir Alsiraj