  Motivation: A Genomic Dictionary, i.e., the set of the k-mers appearing in a
genome, is a fundamental source of genomic information: its collection is the
first step in strategic computational methods ranging from assembly to sequence
comparison and phylogeny. Unfortunately, it is costly to store. This motivates
some recent studies regarding the compression of those k-mer sets. However,
such an area does not have the maturity of genomic compression, lacking an
homogeneous and methodologically sound experimental foundation that allows to
fairly compare the relative merits of the available solutions, and that takes
into account also the rich choices of compression methods that can be used.
  Results: We provide such a foundation here, supporting it with an extensive
set of experiments that use reference datasets and a carefully selected set of
representative data compressors. Our results highlight the spectrum of
compressor choices one has in terms of Pareto Optimality of compression vs.
post-processing, this latter being important when the Dictionary needs to be
decompressed many times. In addition to the useful indications, not available
elsewhere, that this study offers to the researchers interested in storing
k-mer dictionaries in compressed form, a software system that can be readily
used to explore the Pareto Optimal solutions available r a given Dictionary is
also provided.
  Availability: The software system is available at
https://github.com/GenGrim76/Pareto-Optimal-GDC, together with user manuals and
installation instructions.
  Contact<EMAIL_ADDRESS>  Supplementary information: Additional data are available in the Supplementary
Material.
