Hi Carlos, if you are planning to use the Pfaffl method you could use them all at once with Qiagen REST 2009 software.

Best of luck

Thanks Daniel!  I am manually using ddCT (2ddCT) method, and REST 2009 for analysis. Best regards,

Hi Carlos,

following Jo Vandesomple method for 2DDCt data normalization, the best choice is geometric averaging of multiple internal control genes, rather than common average (mean) or individual normalization. There are some softwares already including this normalization method, mainly qBase from Biogazel, but I'm not sure about REST.

I attached the paper but, in case it doesn't work, this is the reference.

Genome Biol. 2002

Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

Vandesompele J1, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F.

Hope it helps!

thank you so much for sharing your knowledge Silvia. I will check the paper. With my best wishes,

Remember that housekeeping genes don't always show stable expression across all cell types, maturation gradients or under stress conditions. You need to identify the right set of reference genes for your particular experiment.

Thanks Richard. I read something about there is not an "universal reference gene", but the question is, How we can identify a right set of reference genes? The best for 2015.

Hi again Carlos,

an appropriate reference gene is this with the lowest variability (ideally zero) between your samples/conditions. To test it, just follow the 2DCt method (be careful, not 2DDCt) described by Livak and Schmittgen to calculate the variability among samples/conditions:

Methods. 2001 Dec;25(4):402-8.

Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Livak KJ1, Schmittgen TD.

As a trick, if there's available array data in an identical model to yours (e.g. in GEO) you could start by calculating the 2DCt of some of the invariable genes.

Totally agree with Richard. Be careful with the so called standard reference genes, such as gapdh or actin. It is generally wiser to choose ribosomal proteins or elongation factors for some applications such as developmental studies.

It depends on your model but it would be advisable to perform a pubmed search for validated ref genes in your model.

All the best

Hi Silvia and Daniel, thank you so much for your time. Your comments are very useful for me. I used GAPDH, Actin, and RPS18 in a model of EBV-transformed lymphoblastoid cell line. I used ddCT method and REST 2009 platform with consistent results. All the best for 2015,