I get fold change of miRNAs expression after running qPCR. I would like to know whether I need to do statistical analysis for those fold change or not?
in fold change, if expression level is above 1, it is significant. There is already defined value.
Would like to know experts' opinions and how do you do such analysis. Appreciate with your paper or recommended papers to view. Thanks.
Hi Jamail,
You will certainly have some trouble trying to publish your results without proper statistical tests. Even if you consider a fold change higher than 1 as biologically relevant, you should still check if the difference you see is caused by chance. So, I would recommend you to plan the qPCRs so you can have biological, independent replicates. Unless you have a very particular case, you can probably look up for Student's t-test or ANOVA (and some post-hoc tests), depending on the number of groups you intend to compare. Since you are expressing your results as fold change, you should also have a look into one sample t-test, which compares one group against one predetermined value (usually 1 or 100%).
That is the short answer. Maybe you can tell more about your experimental setup, so we can give some more specific tips.
Best of luck with your qPCR!
I agree with the above answer. Only, let me comment more on this:
"in fold change, if expression level is above 1, it is significant. There is already defined value."
this is false. First, what do you consider as fold change? the ratio or the log2 of the ratio? In the first case, a ratio above 1 simply means that the miRNA is more abundant in the sample that goes at the numerator. In case you consider the log2 of the ratio, 1 means a doubling, so, you can't tell about significance but it starts to be quite a big change. BUT, if you don't know how much variable is your measure (using, as suggested, biological replicates) you can't know if a difference is significant or not. Let's suppose you know that the average height in humans is 1.7 meters. is someone measuring 1.9m significantly different from the average? Simply we can't tell without knowing the dispersion of the distribution around the mean. For instance suppose you have a standard deviation of 0.18m in the human population, then 13% of the people will be as tall or taller than that. Otherwise, if the standard deviation is 0.05, then you would observe a person of 1.9m or more every ~316'000 people, which makes it a little bit more extreme.
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