Plant improvement requires selection, which can be complicated when the genetic basis of a trait is complex or poorly understood. In an effort to better understand the genetic control of potato (Solanum tuberosum) tuber composition, we performed non-targeted metabolomic profiling to generate a deep (but largely anonymous) dataset, and analyzed the data with a combination of genetic and network approaches. Water/methanol extracts of cooked potato tuber cores from 185 clones that had previously been genotyped by the Solanaceae Coordinated Agricultural Project (SolCAP) were analyzed by LC/MS-MS; this resulted in the detection of 981 features that represent a mixture of primary metabolites, specialized metabolites and hydrolyzed fragments of abundant proteins. Using GWASpoly, an R package that considers gene dosage through a series of genetic models, 472 features could be associated with at least one single nucleotide polymorphism (SNP) marker, markedly increasing the number of marker-trait associations that have been made in potato to date. Unexpectedly, SNPs associated with features were not uniformly distributed throughout the genome, but were instead clustered on chromosomes 3, 7, and 8, with dozens of features associated with several small (~2 Mbp) regions. Also of note was that the most significant SNPs for several glycoalkaloids (α-chaconine, β-chaconine, and α-solamarine) – detected on chromosomes 2, 7, and 8 – are unlinked to any known glycoalkaloid biosynthetic genes. Network analysis condensed the 981 features into 44 modules, whose eigenvalues were then used to explore correlations with phenotype data collected by SolCAP, as well as for genetic mapping. Half of the modules were associated with at least one SNP according to GWAS; 11 of these were also significantly correlated with chip color. Loci associated with module eigenvalues were not evenly distributed throughout the genome, but like individual features, were instead clustered on chromosomes 3, 7 and 8. Unexpectedly, the features within modules were structurally disparate, suggesting that linkage disequilibrium confounds network analyses in potato. This research expanded the number of known marker-traits associations in potato by more than 50-fold, and identified potential selection targets to modify potato chip quality and glycoalkaloid content by identifying genetic markers correlated with these traits.