title: Prioritising risk pathways of complex human diseases based on functional profiling.
abstract: Analysis of the biological pathways involved in complex human diseases is an important step in elucidating the pathogenesis and mechanism of diseases. Most pathway analysis approaches identify disease-related biological pathways using overlapping genes between pathways and diseases. However, these approaches ignore the functional biological association between pathways and diseases. In this paper, we designed a novel computational framework for prioritising disease-risk pathways based on functional profiling. The disease gene set and biological pathways were translated into functional profiles in the context of GO annotations. We then implemented a semantic similarity measurement for calculating the concordance score between a functional profile of disease genes and a functional profile of pathways (FPP); the concordance score was then used to prioritise and infer disease-risk pathways. A freely accessible web toolkit, 'Functional Profiling-based Pathway Prioritisation' (FPPP), was developed (http://bioinfo.hrbmu.edu.cn/FPPP). During validation, our method successfully identified known disease-pathway pairs with area under the ROC curve (AUC) values of 96.73 and 95.02% in tests using both pathway randomisation and disease randomisation. A robustness analysis showed that FPPP is reliable even when using data containing noise. A case study based on a dilated cardiomyopathy data set indicated that the high-ranking pathways from FPPP are well known to be linked with this disease. Furthermore, we predicted the risk pathways of 413 diseases by using FPPP to build a disease similarity landscape that systematically reveals the global modular organisation of disease associations.
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
authors.forename: Teng
authors.initials: T
authors.lastname: Huang
authors.forename: Yun
authors.initials: Y
authors.lastname: Xiao
authors.forename: Shangwei
authors.initials: S
authors.lastname: Ning
authors.forename: Peng
authors.initials: P
authors.lastname: Wang
authors.forename: Qianghu
authors.initials: Q
authors.lastname: Wang
authors.forename: Xin
authors.initials: X
authors.lastname: Chen
authors.forename: Xu
authors.initials: X
authors.lastname: Chaohan
authors.forename: Donglin
authors.initials: D
authors.lastname: Sun
authors.forename: Xia
authors.initials: X
authors.lastname: Li
authors.forename: Yixue
authors.initials: Y
authors.lastname: Li
mesh_terms: D000465:Algorithms; D002311:Cardiomyopathy, Dilated / Q000235:genetics; D016000:Cluster Analysis; D004194:Disease / Q000235:genetics*; D020869:Gene Expression Profiling; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D006801:Humans; D015203:Reproducibility of Results; D012307:Risk Factors; D015398:Signal Transduction / Q000235:genetics*