In order to find genetic and metabolic pathways related to phenotypic traits of interest, we analyzed gene expression data, metabolite data obtained with GC-MS and LC-MS, proteomics data and a selected set of tuber quality phenotypic data from a diploid segregating mapping population of potato. In this study we present an approach to integrate thesexe2x80x89~xe2x80x89omics data sets for the purpose of predicting phenotypic traits. This gives us networks of relatively small sets of interrelatedxe2x80x89~xe2x80x89omics variables that can predict, with higher accuracy, a quality trait of interest.