Local sequence alignments statistics: deviations from Gumbel statistics in the rare-event tail

Background: The optimal score for ungapped local alignments of infinitely long random sequences is known to follow a Gumbel extreme value distribution. Less is known about the important case, where gaps are allowed. For this case, the distribution is only known empirically in the highprobability region, which is biologically less relevant. Results: We provide a method to obtain numerically the biologically relevant rare-event tail of the distribution. The method, which has been outlined in an earlier work, is based on generating the sequences with a parametrized probability distribution, which is biased with respect to the original biological one, in the framework of Metropolis Coupled Markov Chain Monte Carlo. Here, we first present the approach in detail and evaluate the convergence of the algorithm by considering a simple test case. In the earlier work, the method was just applied to one single example case. Therefore, we consider here a large set of parameters: We study the distri...

• Type: Journal
• Year: 2007
• Where: ALMOB
• Authors: Stefan Wolfsheimer, Bernd Burghardt, Alexander K. Hartmann
• Keywords: ALMOB 2007, Gumbel Distribution, Gumbel Extreme Value, Local Alignments