Shuffling Biological Sequences

This paper considers the following sequence shuffling problem: Given a biological sequence (either DNA or protein) s, generate a random instance among all the permutations of s that exhibit the same frequencies of k-lets (e.g, dinucleotides, doublets of amino acids, triplets etc.). Since certain biases in the usage of k-lets are fundamental to biological sequences, effective generation of such sequences is essential for the evaluation of the results of many sequence analysis tools. This paper introduces two sequence shuffling algorithms: A simple swappingbased algorithm is shown to generate a near-random instance and appears to work well, although its efficiency is unproven; a generation algorithm based on Euler tours is proven to produce a precisely uniform instance, and hence solve the sequence shuffling problem, in time not much more than linear in the sequence length. 1 Introduction Computational analysis of biological sequences (or "strings") has become an invaluable tool in mo..