Hi, Biostars!
Can anyone tell me how to validate the RNA-Seq Differential gene expression data using qPCR?
How many genes should I select for qPCR validation?
Is there any criteria for selecting the differentially expressed genes for qPCR validation?
and finally what is the best method to visualize/represent the correlation between RNA-Seq and qPCR data?
Hey!
It's highly recommendable to validate at least 20 genes.
I'd suggest to choose the ones interesting for the topic you are addressing in your study and ones completely random, or for which you observed an interesting behaviour.
The method is a simple Pearson correlation between the two groups: 1: RNA-Seq data and 2: qPCR data. If you got a Pearson correlation value of min 0.7 consider your validation already quite good! Good luck!
The wise way is to have a look to the latest papers in your topic and to the related journal requirements. Then you can figure out what do you precisely need for your purpose
Wondering again why we keep thinking that validation with qPCR is required for our RNA-Seq experiments. I think time of changes have to come in the sense that we should consider even the opposite, that is, that we should use RNA-Seq information to validate our qPCR experiments
RNA-Seq relay in the single fact that a sequence read, as long as 100 or 150 bases is undoubtedly mapped to our genome or transcriptome. If error arises from sequencing, this mapping does not take place. We can always take into account the quality of mapping and the flag values to filter our mapped reads to get rid of soft and hard clipping that could be discarded. In fact, this filtering should be imperative in my opinion.
In any case, it is certain that RNA-Seq is not a fully bulletproof method. But... If we compare the many different issues that arise from a qPCR experiment such as is the RNA degraded along the experiment?, is there any other complementary RNA hybridizing with mine that interferes with the amplification ?, how well the primers align ?, is there any GC or bias base composition that interferes with amplification ?. Are my reagents and enzyme in good condition?, is my device clean enough to accurately do the measurements ?. Is my assembled genome accurate enough?. These are some examples that in my opinion demonstrate that much many issues can affect qPCR
Hi lessismore, Thank you for your answer. Is there any standard guideline for valiadting the RNASeq data using qPCR?
The wise way is to have a look to the latest papers in your topic and to the related journal requirements. Then you can figure out what do you precisely need for your purpose
Hello!, May you give to me some reference about these?
thanks!