real time PCR analysis in patient samples - (Jul/23/2012 )

Hi all,
I am using quantitative real time PCR for a particular gene in vein tissue of 20 patients and 20 healthy subjects. I use an endogenous control also. I do gene Ct minus endogenous Ct so as to get delta Ct.

My real doubt starts here, how will i compare this result in patients with control. Detla Ct value is present for 20 individual controls , which one i take for comparing with my patient Ct?
or if taking average of Ct of controls and then use it for comparing patients, will it be a normal way to do? Ct will change in healthy individuals greatly, since it is not like control cell culture samples.
While checking similar papers, they have not discussed the analysis properly with no description.
In some papers, I have also seen charts with gene/endogenous control mRNA fold. I am also unaware of how to calculate mRNA fold?
Hope someone will help me
Thankyou for anticipation of response
Looking forward

It sounds like you just want to use the delta-delta Ct method to calculate relative quantities (RQ) of the two genes in each patient. Using this method you can pick one healthy donor to set as RQ=1 and then you will calculate the RQ of the two genes for all of the other patients and healthy donors.

For individual patient studies like this statistical significance may be hard to establish. It may be best to just plot the data points side by side so that you can see the distribution.

Usual way to dal with patient control samples is pooling. You take the same amount of all your healthy samples and mix it together. This is called pool.
You then normalise your patient samples to the pool sample, normal delta-delta Ct method of efficiency corrected Pfaffl, whatever suits you better.

However, you noticed yourself there would be certain variability between different healthy controls. I would measure the healthy samples also, individually, normalise to the pool, and by this you get a range of controls. You see it's not actually true, that you have one value for "normal" you have a range of normals.

You now have a group of patient values and group of control values, you can put it in box-and-whiskers graph for example to see significance.

Or you can make a cutoff delimited by the fold changes of controls, but I'm affraid mostly the variability within controls is quite big to just say you only take values outside the control range. I would go for the graph.