For two list of dependent data X and Y, we want to test X < Y.
The pairwised t-test is inappropriate because it violates independence assumption.
Bootstrap or permutation can only be used when there the list of observations are long.
For our H2O2-LOH dataset, we have only 10 time points (H2O2 doses), so bootstrap and permutation is inappropriate as well.
W Wu suggests that Fisher's exact test can be applied for each time point, and then apply Bonferroni correction. We think 3/4 LOH suggest a positive dependence between 1/2 and 1/4 LOH.
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