There are different methods of representing the results, which is the most reliable method?
Like Chinmaya, I also use 2∆ct method.
As for the presentation, I use "Relative mRNA level" in Y-axis. Its pretty common in our field.
I hope that helps.
Hi Eman, I've been using the Pfaffl method since forever and I like to present the data as DeltaCt rather than DeltaDeltaCt (also referred to as fold induction). The former way of presenting the data indeed gives you the chance to show also differences in the expression levels of your gene of interest, with respect to the housekeeping gene, in control samples/genotypes. This is an important piece of information that you may miss if you present your data as DeltaDeltaCt only.
Dear Eman
- I cannot add to the answers above, which I concur with
- I have provided you with a worked example of the Livak or delta delta Ct method
- I will also make explicit that the Livak or delta delta Ct method pre supposes a near perfect doubling; Hence using 2(^x) where X = your delta delta Ct integer
- In fact to utilise the Livak method your % efficiencies derived from standard curves should lie ideally between 90% -110% but at the very least exceed 85% in my experience
- What is more your GOI standard curves and housekeeping standard curves should ideally fall within 5% of one another
- If respective efficiencies fall below 85% and/or your respective GOI and housekeeping % deviate by more than 5% than as mentioned you can plus your actual % in into the Pfaffl equation which 'corrects' for these discrepancies
See also a prior answer of mine:
https://www.researchgate.net/post/Which_arithmetic_formula_I_should_use_to_analyze_real_time_data#view=57a1b20c217e20ba8c7706fe
Dear Eman, I have used both 2∆ct method and Pfaffl methods and Pfaffl is a good choice.. for software, you can use the same software provided with the machine and then the graphpad... but use DeltaCt to show all expressions wrt housekeeping gene
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