geNorm and normalising factor - (Jul/16/2008 )

Hi

I am using Real time RT-PCR. I use and i cycler and I generate a standard curve (for acceptance it should be between -3 and -3.5) for gene of interest and reference/house keeping gene (18S or 28S). I use triplicate measurements for standard and samples.
I do the normalisation by deviding the STARTING QUANTITY MEAN of GENE OF INTEREST by STARTING QUANTITY MEAN of REFERENCE GENE. I really want to know how the normalising factor in geNorm can be used with this method, if I choose to include several more reference genes? please anyone there who is using the same method as I am and have used geNorm ?? pleae help I also would like to know how I am supposed to do the normalising if I use more than one reference gene??

thanx

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you can find the formulas in the attached paper.

in short (if i have understood correct):

you calculate your deltaCt Values of your GOI and your HKGs-> Ct(calibrator) - Ct(sample)

Then you calculate the relative quantity: RQ = 2(or your appropriate base according to your efficiency)^deltaCt

Next, you calculate your normalizaztion factor (NF) of your HKGs: NF = extract the n root of the geometric mean of your HKG RQ values (n = number of HKGs).

Calculate the normalized relative quantities (NRQ): RQ (gene of interest)/NF

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Thanks Ned land,

I have one more question

All this time in our lab We have been doing RT-PCR and for normalisation we have included corresponding reference gene triplicates IN EVERY PCR PLATE. I got to know that this is a common misconception in RT-PCR . it seems most groups take reading once, from reference gene for a Particular cDNA synthesis and keep on using these values until them make new cDNA again.

I am shocked how much reagents and sample cDNA we have been wasting. Does any one has any logical reasoning for repeating 18s triplicates with every run?? I am just wondering if there is a justification for this.

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Hi ned Land,

I use relative standard curve method and divide the sq-mean value of GOI by the ref gene sq-mean value.

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