X Raymond Gao1, Hua Huang2. 1. Department of Ophthalmology and Visual Science, Department of Biomedical Informatics, and Division of Human Genetics, The Ohio State University, Columbus, OH 43212, USA. 2. Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA, USA.
Abstract
SUMMARY: Pleiotropy plays an important role in furthering our understanding of the shared genetic architecture of different human diseases and traits. However, exploring and visualizing pleiotropic information with currently publicly available tools is limiting and challenging. To aid researchers in constructing and digesting pleiotropic networks, we present PleioNet, a web-based visualization tool for exploring this information across human diseases and traits. This program provides an intuitive and interactive web interface that seamlessly integrates large database queries with visualizations that enable users to quickly explore complex high-dimensional pleiotropic information. PleioNet works on all modern computer and mobile web browsers, making pleiotropic information readily available to a broad range of researchers and clinicians with diverse technical backgrounds. We expect that PleioNet will be an important tool for studying the underlying pleiotropic connections among human diseases and traits. AVAILABILITY AND IMPLEMENTATION: PleioNet is hosted on Google cloud and freely available at http://www.pleionet.com/.
SUMMARY: Pleiotropy plays an important role in furthering our understanding of the shared genetic architecture of different human diseases and traits. However, exploring and visualizing pleiotropic information with currently publicly available tools is limiting and challenging. To aid researchers in constructing and digesting pleiotropic networks, we present PleioNet, a web-based visualization tool for exploring this information across human diseases and traits. This program provides an intuitive and interactive web interface that seamlessly integrates large database queries with visualizations that enable users to quickly explore complex high-dimensional pleiotropic information. PleioNet works on all modern computer and mobile web browsers, making pleiotropic information readily available to a broad range of researchers and clinicians with diverse technical backgrounds. We expect that PleioNet will be an important tool for studying the underlying pleiotropic connections among human diseases and traits. AVAILABILITY AND IMPLEMENTATION: PleioNet is hosted on Google cloud and freely available at http://www.pleionet.com/.
Authors: Shanya Sivakumaran; Felix Agakov; Evropi Theodoratou; James G Prendergast; Lina Zgaga; Teri Manolio; Igor Rudan; Paul McKeigue; James F Wilson; Harry Campbell Journal: Am J Hum Genet Date: 2011-11-11 Impact factor: 11.025
Authors: Joseph K Pickrell; Tomaz Berisa; Jimmy Z Liu; Laure Ségurel; Joyce Y Tung; David A Hinds Journal: Nat Genet Date: 2016-05-16 Impact factor: 38.330