I read through the supplemental materials in the first post as well as a few other resources, but still have a question as to how best accomplish my objective.
My question is how to best compare many samples with many genes. My objective is to get a relative comparison of gene levels between approximately 15 samples and approximately 12 primer sets, one of which is GAPDH which our lab uses as the reference gene.
Two strategies come to mind:
I can run on a single plate, triplicate of each sample (15 samples * 3 = 45 wells) for GAPDH and one gene of interest (45 wells for GAPDH + 45 wells for gene #1 = 90 wells). I would then need to run one plate for each gene to be tested for a total of 12 pcr plates (plate 1: GAPDH vs gene #1, plate 2: GAPDH vs gene #2, etc)! I would use the Pfaffl method (a modified delta-delta-Ct method) on each plate to get a comparison of the gene of interest expression level relative to the GAPDH level. At the end, I would plot those fold-changes in one graph showing the relative level of each gene in each sample. I feel that I can combine the data from the multiple plates since the reference (GAPDH) is run on every plate, so each plate is telling me the fold change of one gene relative to GAPDH levels.
I would of course run a dilution series of each gene separately to get the accurate efficiency so I can use the Pfaffl method.
I can run on a single plate, one sample with each primer set, in triplicate (12 primer sets * 3 = 36 wells). I can then fit two samples per plate (36 wells for sample #1 + 36 wells for sample #2 = 72 wells), assaying all the gene levels for each sample. This way, I have to run only 8 pcr plates in total (plate 1: samples #1 and #2, plate 2: samples #3 and #4, etc). In the end, I would overlay the results - they should be comparable since what I am reporting is the expression level relative to GAPDH for each gene in each sample.
My only hesitation here is that, what if hte GAPDH levels between two samples is different? Theoretically, it shouldn't matter too much since that is what I am normalizing to.
Edited by JohnAlexander, 09 November 2010 - 12:24 PM.