How to assess if biological measurements follow a normal or a log-normal distribution
From personal experience, nearly all count data whether from microarray or reads from RNAseq of some kind, requires a log transformation of the counts. Usually a small fraction is added to all values before doing so to zero protect. Log2(counts + 0.5) or some such.   This is independent of the treatments. If you log transform one sample, you will do the same for all samples. To examine for normality, a simple way is to look at the histogram of counts (by all samples or by each sample) before and after transformation. Roughly bell shaped -> proceed.  

Pictures below from my data. Although the data are from RNAseq, microarray data should be similar. 

R code here:

hist(t$counts,breaks=100,main="Histogram of Raw Counts from RNAseq")
hist(log(t$counts + 0.5,2),breaks=100,main="Histogram of Log2
transformed Counts from RNAseq")