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Open Access Highly Accessed Research article

Systematic analysis, comparison, and integration of disease based human genetic association data and mouse genetic phenotypic information

Yonqing Zhang1, Supriyo De1, John R Garner1, Kirstin Smith1, S Alex Wang2 and Kevin G Becker1*

Author affiliations

1 Gene Expression and Genomics Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224 USA

2 Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, MD 20892 USA

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Citation and License

BMC Medical Genomics 2010, 3:1  doi:10.1186/1755-8794-3-1

Published: 21 January 2010

Abstract

Background

The genetic contributions to human common disorders and mouse genetic models of disease are complex and often overlapping. In common human diseases, unlike classical Mendelian disorders, genetic factors generally have small effect sizes, are multifactorial, and are highly pleiotropic. Likewise, mouse genetic models of disease often have pleiotropic and overlapping phenotypes. Moreover, phenotypic descriptions in the literature in both human and mouse are often poorly characterized and difficult to compare directly.

Methods

In this report, human genetic association results from the literature are summarized with regard to replication, disease phenotype, and gene specific results; and organized in the context of a systematic disease ontology. Similarly summarized mouse genetic disease models are organized within the Mammalian Phenotype ontology. Human and mouse disease and phenotype based gene sets are identified. These disease gene sets are then compared individually and in large groups through dendrogram analysis and hierarchical clustering analysis.

Results

Human disease and mouse phenotype gene sets are shown to group into disease and phenotypically relevant groups at both a coarse and fine level based on gene sharing.

Conclusion

This analysis provides a systematic and global perspective on the genetics of common human disease as compared to itself and in the context of mouse genetic models of disease.