[R] permutated p values vs. normal p values

[Steve Adams]

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? 


Thanks