  Addressing the functionality of genomes is one of the most important and
challenging tasks of today's biology. In particular the ability to link
genotypes to corresponding phenotypes is of interest in the reconstruction and
biotechnological manipulation of metabolic pathways. Over the last years, the
OmniLogTM Phenotype Microarray (PM) technology has been used to address many
specific issues related to the metabolic functionality of microorganisms.
However, computational tools that could directly link PM data with the gene(s)
of interest followed by the extraction of information on genephenotype
correlation are still missing. Here we present DuctApe, a suite that allows the
analysis of both genomic sequences and PM data, to find metabolic differences
among PM experiments and to correlate them with KEGG pathways and gene
presence/absence patterns. As example, an application of the program to four
bacterial datasets is presented. The source code and tutorials are available at
http://combogenomics.github.io/DuctApe/.
