Visualizing gene determinants of disease in drug discovery

Target discovery, subphenotype detection and the detection of human heterogeneity are major challenges in drug discovery and development on which genetic markers can have an impact. Visualizing gene determinants of traits in case-control study individuals during drug discovery using contrasts of empirically-derived log Bayes factors (LBFs) from whole-genome scan single nucleotide polymorphism (SNP) data is presented to aid this. Examples of the use of eigen analysis, covariate overlays and individualized aggregation to ontologies are included from disease research studies. Displays of individuals, or exposures of biological features of interest, can encompass unlimited numbers of markers in a single multivariate analysis without multiple testing. This filtering approach is aimed at nonspecialists who find themselves asked to undertake work such as that performed by the authors.