MissMax: alignment-free sequence comparison with mismatches through filtering and heuristics.
BACKGROUND
Measuring sequence similarity is central for many problems in bioinformatics. In several contexts alignment-free techniques based on exact occurrences of substrings are faster, but also less accurate, than alignment-based approaches. Recently, several studies attempted to bridge the accuracy gap with the introduction of approximate matches in the definition of composition-based similarity measures.


RESULTS
In this work we present MissMax, an exact algorithm for the computation of the longest common substring with mismatches between each suffix of a sequence x and a sequence y. This collection of statistics is useful for the computation of two similarity measures: the longest and the average common substring with k mismatches. As a further contribution we provide a "relaxed" version of MissMax that does not guarantee the exact solution, but it is faster in practice and still very precise.
Department of Information Engineering, University of Padova, via Gradenigo 6/a, 35131 Padova, Italy.
Cinzia
0000-0002-6616-4003
C
Pizzi
Alignment free; Compositional approaches; Mismatches; Phylogenetic analysis; Sequence similarity