I am checking the relative expression of 10 genes via qPCR between control and patient cell lines (iPSC vs. NSC vs. Neurons). After analysis I have obtained:
a. 2-ΔCt values for each cell line which I have plotted as 3 grouped bar graph for each line (multiple t-test)
b. ΔΔCt
c. 2-ΔΔCt (fold change?)
Please help me represent b & c in the most useful way also, feedbacks on a. (particularly statistical analysis) would be greatly appreciated
Thanks in advance.
error bars represent SEM.
Hi Bilal,
What is your control/ reference / endogenous gene of interest ? I hope you have already calculated ΔCt in part (a) to see the change in the gene expression of your target vs control gene in your test samples.
In part (b) you will compare ΔCt of samples with ΔCt of control.
In part (c) you will calculate log base 2 of your results from part (b).
It would be easier to do this calculation on Excel sheet. And the fold change need to present graphically. I hope you could figure it out.
Good luck!
Rahul Mallick sorry If my question was ambiguous. I have already calculated ΔΔCt , 2-ΔΔCt and have the values. I need help with presentation of the generated data.
Should I plot graphs for ΔΔCt or 2-ΔΔCt? Is there anything wrong with the one already generated (attached)
What statistical tests should I put to use and on what data set? because I have read that one should not do statistical tests on the fold change values.
Thank you.
Dear Bilal
it seems that you normalized all your data to 1. If you have your controls then you can make anova test one way and compare each cell line with there controls first then with others. In this way the figure would be more readable.
regards
Shilan
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