I came across a problem in qPCR data analysis and would appreciate if anybody can help. Basically, 3 biologically independent qPCR experiment is good enough (accepted) to conclude any result. In my experimental condition, I have seen the effect of Gene A on Gene B by 3 times repeating qPCR. (This effect was also observed strongly at protein level by western blotting). For the data analysis since N=3, I can not obtain the normal distribution and thus can not use student t' test (although in many good papers researchers use this test even with n=3). Then I need to go for the non-parametric tests like Mann Whitney U test in such a condition. Unfortunately, Mann Whitney U test does not show any significance which is not true because I have confirmed this effect strongly at protein level and I saw its effect on functionality of the cells. In such condition, student t test gives the best results (***, P < .0001) which is correctly represents the effect but on the other hand this test is statistically incorrect. Mann Whitney U test however is statistically a correct test but definitely gives a false negative result because it does not show the significance of the effect. So I do not know how to solve this problem.This problem is mainly happening because the number of the experiment is low and with performing 2-3 more we can overcome this problem with Mann Whitney U test however due to my condition I can not perform any extra qPCR. Moreover, I have performed several qPCR with different conditions and won't be able to repeat more so should rely on 3 independent experiments only which is basically accepted in qPCR.Would appreciate it for any helpful comments.