Linear-Time Sequence Comparison Using Minimal Absent Words & Applications

Sequence comparison is a prerequisite to virtually all comparative genomic analyses. It is often realised by sequence alignment techniques, which are computationally expensive. This has led to increased research into alignment free techniques, which are based on measures referring to the composition of sequences in terms of their constituent patterns. These measures, such as $q$-gram distance, can usually be computed in time linear with respect to the length of the sequences. In this article, we focus on the complementary idea: how two sequences can be efficiently compared based on information about what does not occur in the sequences. In particular, we present a linear-time and linear-space algorithm to compare two sequences by considering all their minimal absent words. An absent word is minimal if all its proper factors occur in the sequence. In the process, we present some results of combinatorial interest, and also extend the proposed techniques to circular sequences.