Gabi Kastenmüller (Institute of Computational Biology, Helmholtz Zentrum München): Building web-based resources for the dissemination of results from large-scale ome-wide association studies.

Abstract

Over the past decade, an increasing number of large-scale ome-wide association studies such as genome-wide association studies with metabolomics and proteomics traits have identified numerous molecular relationships. For researcher like clinicians or biologists who are, for example, specialized in the role of specific pathways/genes/metabolites in certain disease, these association results can provide valuable starting points for generating concrete functional hypotheses and experiments. To enable researchers with and without bioinformatic capacities to fully leverage the entirety of results from such large association screens, we have been building publicly accessible web-based resources which allow browsing and querying complete result sets. Users can readily explore, contextualize, or extract associations for their “favorite” gene, protein, or metabolites, making results easily accessible, that are relevant for their research question but would have been hidden in supplementary tables or would not have been shared without specific request otherwise. Examples for such resourcs from our studies include: http://www.omicscience.org, http://ukb-ppp.gwas.eu/, http://proteomics.gwas.eu/, http://gwas.eu/si. Our AD Atlas (http://www.adatlas.org) and the SNiPA (http://snipa.org) web-tools go one step further with the integration and annotation of knowledge from publicly available resources across multi-omics layers.