I am analyzing some IHC data on the density of cells in two brain regions(factor 1) in two closely related species(factor 2). My data is composed of an n of 6 for each species and is not normally distributed(Shapiro-Wilk test). so I went for the non-parametric aligned ranks transformation ANOVA (based on the recommendations in: https://rcompanion.org/handbook/F_16.html). Till here everything should be fine but the problem starts from here. After I run the aligned ranks transformation ANOVA I get significant main effects(factor1: P= 0.040, F= 4.377; factor2: P= 0.042, F= 4.287) and a significant interaction between factor1 and factor2 (factor1 X factor2: P= 0.032, F=4.748). Based on these results I expect that the density of my cells will be different in an area and species-specific way. Therefore I conducted some post hoc tests, however, I didn't get any significant value in my post hoc tests. I know this is possible and this might indicate that the associations of species and area are not strictly addictive or that with our sample, it is not possible to specify which differences are responsible for our interaction (or main effects).
Considering all of this and that I know this is a small sample size and I cannot increase it, my question is: how can I handle this situation? From the perspective of a publication, how can I explain these results? could a transformation of my data help us understand where the effects of the ANOVA come from (is this a good approach even?)? Is there any test I can conduct to solve this problem? Should I just report it and that is it or am I missing something that could help me understand the discrepancy between the ANOVA and the post-hocs? If this is the case how should I proceed(please in this case explain it to me as clearly as possible)?
Thank you very much for all the help that could be provided. I saw there are similar questions posted but non of them was my specific case or in non of them i found a real answer that I could understand (maybe due to my lack of knowledge on this tests). Thanks again for any help this will be very helpful for me.