Hi, I am performing Cox proportional hazards regression on a microarray dataset with 15000 genes. The p values generated from the Cox regression (based on normal distribution of large sample theory) showed only 2 genes have a p value less than 0.05. However, when I did a permutation on the dataset to obtained permutated p values, and it turned out about 750 genes had a permutated p value less than 0.05 (that just happens to be equal to the number of significant genes you would expect by chance alone). With that big difference in the number of significant genes, which one should I trusted? and what's reason why such a big difference exists? My dataset is not large in sample size (17 samples), might this be the reason?
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