How to calculate Log2 Fold Change for normalised qPCR data?

Question

[Genosa]

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

Answer 1

[VHahaut]

You can find plenty of nice explanation online (you should consider reading the blog post below):

Computing fold change values for RT-PCR

http://blog.mcbryan.co.uk/2013/06/qpcr-normalisation.html

[Genosa]

Got it. Thanks very much

Answer 2

[Kevin Blighe]

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:

1. a housekeeper gene (or genes) within the same sample
2. 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