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Spaced seeds have been recently shown to not only detect more alignments, butalso to give a more accurate measure of phylogenetic distances (Boden et al.,2013, Horwege et al., 2014, Leimeister et al., 2014), and to provide a lowermisclassification rate when used with Support Vector Machines (SVMs) (On-oderaand Shibuya, 2013), We confirm by independent experiments these two results,and propose in this article to use a coverage criterion (Benson and Mak, 2008,Martin, 2013, Martin and No{\'e}, 2014), to measure the seed efficiency in bothcases in order to design better seed patterns. We show first how this coveragecriterion can be directly measured by a full automaton-based approach. We thenillustrate how this criterion performs when compared with two other criteriafrequently used, namely the single-hit and multiple-hit criteria, throughcorrelation coefficients with the correct classification/the true distance. Atthe end, for alignment-free distances, we propose an extension by adopting thecoverage criterion, show how it performs, and indicate how it can beefficiently computed.

A Coverage Criterion for Spaced Seeds and its Applications to Support Vector Machine String Kernels and k-Mer Distances