I have done this many times and can give you some help.
First you need to determine the efficiency of the qPCR primer set. Set of a 1:10 serial dilution series and run a standard curve protocol. You will need at least 5 points for a standard curve to be very reliable (that's my preference) and include standards with Ct in the range of 15-30. I don't know which machine or software you are using but to start you can just arbitrarily set the standard starting concentration. (If you want absolute quantification later then you will need to create a standard curve of known dilutions - I did mine with an IVT RNA). Once the run is complete the software should give you the standard curve equation in the y=mx+b formula. (you may also create a scatter graph in excel and then put a best-fit line in and get its equation). The qPCR efficiency should be between 90-110% to be optimal. The efficiency is calculated from the slope as E=10^(-1/slope), E% = (E-1) x 100%. for a 10x serial dilution series an ideal slope is -3.32. the R-squared value should also be >0.95. It make take adjusting primers or primer concentrations to achieve a good standard curve.
Now you know the efficiency of you qPCR and want to do calculations. If you are comparing 2 different primer sets (like one fore gene X and one for Gene Y) then as long as the efficiencies are similar then you can use the Livak method, 2-ΔΔCq.
If the efficiencies are different then you have to use the Pfaffl method to take this into account. There is a brief description of this here:
http://www.bio-rad.com/en-us/applications-technologies/real-time-pcr-experimental-design#5
and you can visit the website
http://www.gene-quantification.info/
for much more detailed information.
Hope that helps!
I have done this many times and can give you some help.
First you need to determine the efficiency of the qPCR primer set. Set of a 1:10 serial dilution series and run a standard curve protocol. You will need at least 5 points for a standard curve to be very reliable (that's my preference) and include standards with Ct in the range of 15-30. I don't know which machine or software you are using but to start you can just arbitrarily set the standard starting concentration. (If you want absolute quantification later then you will need to create a standard curve of known dilutions - I did mine with an IVT RNA). Once the run is complete the software should give you the standard curve equation in the y=mx+b formula. (you may also create a scatter graph in excel and then put a best-fit line in and get its equation). The qPCR efficiency should be between 90-110% to be optimal. The efficiency is calculated from the slope as E=10^(-1/slope), E% = (E-1) x 100%. for a 10x serial dilution series an ideal slope is -3.32. the R-squared value should also be >0.95. It make take adjusting primers or primer concentrations to achieve a good standard curve.
Now you know the efficiency of you qPCR and want to do calculations. If you are comparing 2 different primer sets (like one fore gene X and one for Gene Y) then as long as the efficiencies are similar then you can use the Livak method, 2-ΔΔCq.
If the efficiencies are different then you have to use the Pfaffl method to take this into account. There is a brief description of this here:
http://www.bio-rad.com/en-us/applications-technologies/real-time-pcr-experimental-design#5
and you can visit the website
http://www.gene-quantification.info/
for much more detailed information.
Hope that helps!
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1274258/pdf/1471-2105-6-62.pdf
kndly read this article
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