minimum replicate for qpcr? - (Apr/13/2011 )
It's always better to calculate with efficiencies. But you don't need to do a standard curve method to get relative quantity in that case, use Pfaffl equation, it's like delta-delta, but with efficiency (Pfaffl, M. (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Research 29 (9): 00-06).
If you have too many samples, and they don't fit to one plate you can have more runs, but you must include the same calibrator sample on every plate and normalise to the one on the same plate. This way you can have more samples.
Trof on Thu Apr 21 13:49:55 2011 said:
It's always better to calculate with efficiencies. But you don't need to do a standard curve method to get relative quantity in that case, use Pfaffl equation, it's like delta-delta, but with efficiency (Pfaffl, M. (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Research 29 (9): 00-06).
If you have too many samples, and they don't fit to one plate you can have more runs, but you must include the same calibrator sample on every plate and normalise to the one on the same plate. This way you can have more samples.
\Thank you for your recommendation!
I've read that paper. Crossing point mentioned in that paper= threshold cycle and ctrl sample=calibrator sample? For this model, we still need to normalise the target expression with ref expression. Still, the ref gene doesn't have to be in the same plate with target?
I am conducting 1 step qPCR. IS this model suitable for me? Because it said "...1 step RT-PCR models are not applicable..." I am not sure whether it means that this model is not suitable for 1 step or it simply meant that 2 step is more efficient than 1 step.
hianghao on Sun Apr 24 14:49:07 2011 said:
Crossing point mentioned in that paper= threshold cycle and ctrl sample=calibrator sample? For this model, we still need to normalise the target expression with ref expression. Still, the ref gene doesn't have to be in the same plate with target?
Yes, Cp = Ct and control = calibrator. No, you still don't need to have all genes in one plate, that's same for any relative quantification. You doesn't even need to run dilution series (for calculating efficiencies) on the same plate, they can be run separate.
hianghao on Sun Apr 24 14:49:07 2011 said:
I am conducting 1 step qPCR. IS this model suitable for me? Because it said "...1 step RT-PCR models are not applicable..." I am not sure whether it means that this model is not suitable for 1 step or it simply meant that 2 step is more efficient than 1 step.
It says it's not applicable for their experiment with different RT efficiencies. It only says that in 1-step there is always bigger variability due to different RT conditions.
Trof on Tue Apr 26 07:58:00 2011 said:
hianghao on Sun Apr 24 14:49:07 2011 said:
Crossing point mentioned in that paper= threshold cycle and ctrl sample=calibrator sample? For this model, we still need to normalise the target expression with ref expression. Still, the ref gene doesn't have to be in the same plate with target?
Yes, Cp = Ct and control = calibrator. No, you still don't need to have all genes in one plate, that's same for any relative quantification. You doesn't even need to run dilution series (for calculating efficiencies) on the same plate, they can be run separate.
hianghao on Sun Apr 24 14:49:07 2011 said:
I am conducting 1 step qPCR. IS this model suitable for me? Because it said "...1 step RT-PCR models are not applicable..." I am not sure whether it means that this model is not suitable for 1 step or it simply meant that 2 step is more efficient than 1 step.
It says it's not applicable for their experiment with different RT efficiencies. It only says that in 1-step there is always bigger variability due to different RT conditions.
Thank you for your advise! So no, you don't need to have same Ta.
In theory, at least, this shouldn't matter if you normalise your results with a housekeeping gene which remains constant.
I am going to use Pfaffl formula for calculation. Should i sum up all replicates to get the mean then only substitute the value into the formula? But there might be differences in concentration of some biological replicates. Or i should do the calculation separately for each replicate, then only calculate the mean value?