We have seen that Karlin's approximations are often far too conservative to give accurate results, but what about the ranking ? Table 3 proposes the Kendall's tau rank correlation (see [16] chapter 14.6 for more details) which is equal to 1.0 for a complete rank agreement and equal to -1.0 for a complete inverse rank agreement. As we will certainly be interested in the most significant sequences produced by our study, we compute our Kendall's tau only on these sequences. When all sequence lengths are considered, Karlin's approximations show their total irrelevance to give correct ranking for the first 10 or 50 most significant p-values. Even when the 100 first p-values are taken into account, relative ranks given by Karlin's approximations are wrong in 63% of the cases, which is huge. However, in the case where the approximations values are close to the exact ones (sequence lengths greater than 2 000, which correspond only to 0.5% of the database), p-values obtained with both methods are highly correlated.