As an assay output we measure expression of one gene per well in a 96 well cell culture plate at different time points/conditions. Eventually, what we have is a matrix (genes x conditions) of gene expression values and we compute the fold change when compared to the control condition. We have one control per condition.
Are there any other better normalization strategies for such experiments?
Is it valid to visualize this data by computing Z-Scores? I have this question for the following reasons:
- because the Z Score is computed on Fold Change which is essentially a positive value.
- unlike RNA Seq the expression of each gene is measured individually (more like qRT PCR for each gene).
PS: If I complicated the experiment design (above) for , then to simplify, I have qRT PCR measurements for many genes in different conditions. Essentially this is expression values and my question is about how to normalize and visualize this data? Computing Fold Change from Control and then applying Z Score... Is it valid?
Suggestions welcome! Thank you very much!