A Resource of Quantitative Functional Annotation for Homo sapiens Genes

Author:

Taşan Murat12,Drabkin Harold J3,Beaver John E2,Chua Hon Nian12,Dunham Julie1,Tian Weidong4,Blake Judith A3,Roth Frederick P11256

Affiliation:

1. Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario M5S-3E1, Canada

2. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115

3. Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, Maine 04609

4. Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200433, P. R. China

5. Center for Cancer Systems Biology, Dana Farber Cancer Institute, Boston, Massachusetts 02115

6. Samuel Lunenfeld Research Institute, Mt. Sinai Hospital, Toronto, Ontario M5G-1X5, Canada

Abstract

Abstract The body of human genomic and proteomic evidence continues to grow at ever-increasing rates, while annotation efforts struggle to keep pace. A surprisingly small fraction of human genes have clear, documented associations with specific functions, and new functions continue to be found for characterized genes. Here we assembled an integrated collection of diverse genomic and proteomic data for 21,341 human genes and make quantitative associations of each to 4333 Gene Ontology terms. We combined guilt-by-profiling and guilt-by-association approaches to exploit features unique to the data types. Performance was evaluated by cross-validation, prospective validation, and by manual evaluation with the biological literature. Functional-linkage networks were also constructed, and their utility was demonstrated by identifying candidate genes related to a glioma FLN using a seed network from genome-wide association studies. Our annotations are presented—alongside existing validated annotations—in a publicly accessible and searchable web interface.

Publisher

Oxford University Press (OUP)

Subject

Genetics(clinical),Genetics,Molecular Biology

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