title: The systems genetics resource: a web application to mine global data for complex disease traits.
abstract: The Systems Genetics Resource (SGR) (http://systems.genetics.ucla.edu) is a new open-access web application and database that contains genotypes and clinical and intermediate phenotypes from both human and mouse studies. The mouse data include studies using crosses between specific inbred strains and studies using the Hybrid Mouse Diversity Panel. SGR is designed to assist researchers studying genes and pathways contributing to complex disease traits, including obesity, diabetes, atherosclerosis, heart failure, osteoporosis, and lipoprotein metabolism. Over the next few years, we hope to add data relevant to deafness, addiction, hepatic steatosis, toxin responses, and vascular injury. The intermediate phenotypes include expression array data for a variety of tissues and cultured cells, metabolite levels, and protein levels. Pre-computed tables of genetic loci controlling intermediate and clinical phenotypes, as well as phenotype correlations, are accessed via a user-friendly web interface. The web site includes detailed protocols for all of the studies. Data from published studies are freely available; unpublished studies have restricted access during their embargo period.
authors.affiliation: Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA.
authors.forename: Atila
authors.initials: A
authors.lastname: van Nas
authors.forename: Calvin
authors.initials: C
authors.lastname: Pan
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Ingram-Drake
authors.forename: Anatole
authors.initials: A
authors.lastname: Ghazalpour
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Drake
authors.forename: Eric M
authors.initials: EM
authors.lastname: Sobel
authors.forename: Jeanette C
authors.initials: JC
authors.lastname: Papp
authors.forename: Aldons J
authors.initials: AJ
authors.lastname: Lusis
keywords: data analysis; data integration; database; genomics; systems biology; web services