title: In silico gene prioritization by integrating multiple data sources.
abstract: Identifying disease genes is crucial to the understanding of disease pathogenesis, and to the improvement of disease diagnosis and treatment. In recent years, many researchers have proposed approaches to prioritize candidate genes by considering the relationship of candidate genes and existing known disease genes, reflected in other data sources. In this paper, we propose an expandable framework for gene prioritization that can integrate multiple heterogeneous data sources by taking advantage of a unified graphic representation. Gene-gene relationships and gene-disease relationships are then defined based on the overall topology of each network using a diffusion kernel measure. These relationship measures are in turn normalized to derive an overall measure across all networks, which is utilized to rank all candidate genes. Based on the informativeness of available data sources with respect to each specific disease, we also propose an adaptive threshold score to select a small subset of candidate genes for further validation studies. We performed large scale cross-validation analysis on 110 disease families using three data sources. Results have shown that our approach consistently outperforms other two state of the art programs. A case study using Parkinson disease (PD) has identified four candidate genes (UBB, SEPT5, GPR37 and TH) that ranked higher than our adaptive threshold, all of which are involved in the PD pathway. In particular, a very recent study has observed a deletion of TH in a patient with PD, which supports the importance of the TH gene in PD pathogenesis. A web tool has been implemented to assist scientists in their genetic studies.
authors: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America.
authors: Yixuan
authors: Y
authors: Chen
authors: Wenhui
authors: W
authors: Wang
authors: Yingyao
authors: Y
authors: Zhou
authors: Robert
authors: R
authors: Shields
authors: Sumit K
authors: SK
authors: Chanda
authors: Robert C
authors: RC
authors: Elston
authors: Jing
authors: J
authors: Li
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics; D005796:Genes / Q000235:genetics*; D056726:Genetic Association Studies; D006801:Humans; D010300:Parkinson Disease / Q000235:genetics; D025941:Protein Interaction Mapping; D012372:ROC Curve; D015203:Reproducibility of Results