Integrating genotypic, molecular profiling, and clinical data to elucidate common human diseases

Abstract

Abstract The identification of genes and, more generally, gene networks underlying common human diseases remain one of the primary objectives in the biomedical and life sciences. Success in reconstructing gene networks underlying complex physiological traits and identifying the key drivers of these traits will largely rest on integrative approaches that combine data from multiple different sources. Key to this integration will be the development and application of sophisticated algorithms to mine the diversity of data. Here we review an integrative genomics approach that enhances the utility of genetics approaches commonly used to dissect complex traits. This integrative genomics approach takes into account genotypic, molecular profiling, and clinical data in segregating populations to identify the key drivers of disease and reconstruct disease‐specific gene networks.