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Motivation: A Genomic Dictionary, i.e., the set of the k-mers appearing in agenome, is a fundamental source of genomic information: its collection is thefirst step in strategic computational methods ranging from assembly to sequencecomparison and phylogeny. Unfortunately, it is costly to store. This motivatessome recent studies regarding the compression of those k-mer sets. However,such an area does not have the maturity of genomic compression, lacking anhomogeneous and methodologically sound experimental foundation that allows tofairly compare the relative merits of the available solutions, and that takesinto account also the rich choices of compression methods that can be used.  Results: We provide such a foundation here, supporting it with an extensiveset of experiments that use reference datasets and a carefully selected set ofrepresentative data compressors. Our results highlight the spectrum ofcompressor choices one has in terms of Pareto Optimality of compression vs.post-processing, this latter being important when the Dictionary needs to bedecompressed many times. In addition to the useful indications, not availableelsewhere, that this study offers to the researchers interested in storingk-mer dictionaries in compressed form, a software system that can be readilyused to explore the Pareto Optimal solutions available r a given Dictionary isalso provided.  Availability: The software system is available athttps://github.com/GenGrim76/Pareto-Optimal-GDC, together with user manuals andinstallation instructions.  Contact: raffaele.giancarlo@unipa.it  Supplementary information: Additional data are available in the SupplementaryMaterial.

Pareto Optimal Compression of Genomic Dictionaries, with or without Random Access in Main Memory