TY - JOUR T1 - The Monarch Initiative: An integrative data and analytic platform connecting phenotypes to genotypes across species JF - bioRxiv DO - 10.1101/055756 SP - 055756 AU - Christopher J Mungall AU - Julie A McMurry AU - Sebastian Köhler AU - James P. Balhoff AU - Charles Borromeo AU - Matthew Brush AU - Seth Carbon AU - Tom Conlin AU - Nathan Dunn AU - Mark Engelstad AU - Erin Foster AU - JP Gourdine AU - Julius O.B. Jacobsen AU - Daniel Keith AU - Bryan Laraway AU - Suzanna E. Lewis AU - Jeremy Nguyen Xuan AU - Kent Shefchek AU - Nicole Vasilevsky AU - Zhou Yuan AU - Nicole Washington AU - Harry Hochheiser AU - Tudor Groza AU - Damian Smedley AU - Peter N. Robinson AU - Melissa A Haendel Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/11/03/055756.abstract N2 - The principles of genetics apply across the whole tree of life: on a cellular level, we share mechanisms with species from which we diverged millions or even billions of years ago. We can exploit this common ancestry at the level of sequences, but also in terms of observable outcomes (phenotypes), to learn more about health and disease for humans and all other species. Applying the range of available knowledge to solve challenging disease problems requires unified data relating genomics, phenotypes, and disease; it also requires computational tools that leverage these multimodal data to inform interpretations by geneticists and to suggest experiments. However, the distribution and heterogeneity of databases is a major impediment: databases tend to focus either on a single data type across species, or on single species across data types. Although each database provides rich, high-quality information, no single one provides unified data that is comprehensive across species, biological scales, and data types. Without a big-picture view of the data, many questions in genetics are difficult or impossible to answer. The Monarch Initiative (https://monarchinitiative.org) is an international consortium dedicated to providing computational tools that leverage a computational representation of phenotypic data for genotype-phenotype analysis, genomic diagnostics, and precision medicine on the basis of a large-scale platform of multimodal data that is deeply integrated across species and covering broad areas of disease. ER -