Sorry if this is a rather basic question. I am trying to find a good solution on how to calculate fold change for qPCR data normalised to housekeepting genes across different conditions.
For example, I have this data: (CT value) Baseline condition Housekeeping gene: 30.7, 30.6, 30.6 Baseline condition Gene X: 33.0, 34.2, 33.5
Treatment condition Housekeping gene: 31.1, 31.4, 31.3 Treatment condition Gene X: 29.1, 29.4, 29.6
After I normalise the baseline condition gene X / Treatment condition gene X to the housekeeping gene by delta-delta CT, what is the correct formula to calculate log2 fold change of treatment over baseline condition please?
Thank you
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Genosa
2 answers
You can find plenty of nice explanation online (you should consider reading the blog post below):
Also an answer here, which corroborates with that given in: Computing fold change values for RT-PCR
The standard is the delta delta Ct (ddCt) method, whereby the Ct values in each sample are normalised to:
- a housekeeper gene (or genes) within the same sample
- the respective values in a control DNA sample
The final, normalised Ct, the delta delta Ct, is then typically put as a negative power to 2:
2 ^ (- ddCt)
For example, we have the following raw Ct values:
SampleRep1 SampleRep2 SampleRep3 | ControlDNA1 ControlDNA2 ControlDNA3
Gene1 19 20 19 | 21 21 20
HousekeeperGene 22 22 22 | 21.5 21 22
Gene1, Delta Ct in Sample = [(19+20+19) / 3] - [(22+22+22) / 3] = -2.667
Gene1, Delta Ct in Control DNA = [(21+21+20) / 3] - [(21.5+21+22) / 3] = -0.8333
Gene1, Delta Delta Ct = -2.667 - (-0.8333) = -1.8337
2 ^ (- ddCt) = 2 ^ (- (-1.8337)) = 3.57 fold increased expression of gene1 in sample1
[from: A: How to report and plot qPCR data ]
Kevin
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