Normalize RNAseq data on RT-dPCR or RT-qPCR

Question

[lagartija]

Hi,

I find a paradox when browsing the litterature : the use of controls such as RT-qPCR (or spike-ins) are supposed to be the golden standard to normalize RNAseq but I cannot find in the litterature good exaples that have used those methods.

Do you know how or which paper have used some references genes expressions measured by RT-qPCR to normalize RNAseq data ?

My initial idea is to use the function estimateSizeFactors from DESeq2 only on the RT-dPCR data and then to apply the factor to the whole RNAseq data. Would that be correct ? I could also try the NORMQ software : https://pmc.ncbi.nlm.nih.gov/articles/PMC7264052/#s0125 but is has no citations... Is there something I am missing ?

Thank you very much in advance for your help :)

[ATpoint]

Is there a reason you do not use standard normalizations for RNA-seq, for example as implemented in edgeR or DESeq2, without further and very custom modifactions?

[lagartija]

I study a cell infected both by a virus and a bacteria at the same time so I suspect there might be many changes in expression. And this would also be the opportunity to test the assumptions behind normalization

[ATpoint]

And this would also be the opportunity to test the assumptions behind normalization

The assumption can be checked on an MA-plot. With qPCR you need to define a reliable reference set of genes which you do not know beforehand reliably.