I have run a qPCR experiment investigating a variety of genes for a time series of samples and was wondering how to calculate my ΔΔct values in relation to this. I have control genes for each sample (gapdh) which vary slightly for each and I have a variety of genes I am testing the expression of. When calculating ΔΔct values I know you are meant to do it relative to your control gene (ie gapdh) and then relative to your control sample. However as I have a time series I do not have a specific control sample as each gene expression pattern varies from time point to time point. Any ideas how to do this please?
I realize that GAPDH is a prominent (maybe the most prominent) "housekeeping" gene to normalize against. Still, I encourage you to check (if possible) your own or some published related RNA-seq datasets towards expression of that gene. I've seen it repetitively in both published and my own data that GAPDH is significantly up/downregulated between conditions. Your normalization might be massively skewed if using GAPDH. I am pretty sure there is literature out there that investigated GAPDH as a normalization control, though I do not have the articles at hand right now. Might be worth checking. If you have (related) RNA-seq data check for properly-expressed genes with strong evidence (e.g. adjusted p-value > 0.5) against differential expression of that gene.
I have other housekeeping control genes and will be normalizing against those also
That is good. If results confirm each other you probably will be fine.