Statistical significance (t-test) - Protein Simulations

#1
Dear board

I am evaluating data from molecular simulations of a protein in two different states (normal and "mutated") and need to check if differences between these states are statistically significant. The simulations were performed as five replicas (by changing random seeds) and for each replica, I measured a property 10'000 times per replica simulation. I use the "stats.ttest_ind_from_stats" method in Python to compute p-values from mean, standard devation (SD), and the number of objects.

Now, I am not sure how to determine the p-values and came up with three possibilities (Methods A-C). Obviosuly, Method A would be my preferred way to do it, as I have a high number of individual measurements and get low p-values (and higher significance of a difference).

What would be the correct way to do it? Any of my "methods" or something different?

I would highly appreciate for a reference, if you have a resolution (as it is scientific work for a publication).

I visualized the problem schematically:
t-test_3.png


Thank you very much for your help!

Best wishes, fisand04
 
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