Log transform data when exporting result
It is good practice to log transform the final gene expression results (i.e. the normalized relative quantities) in order to make the data distribution more symmetrical (as gene expression data is often log normally distributed).
Together with the Central Limit Theorem, this allows the use of parametric statistical tests and calculations that rely on a distribution that resembles a normal distribution (e.g. classic t-test, confidence intervals, Analysis of Variance).
Note that log transformations will not have an adverse affect on non-parametric statistical tests.