Introduction

Identification of key metabolites for complex diseases is a challenging task in today's medicine and biology. A special disease is usually caused by the alteration of a series of functional related metabolites having a global influence on the metabolic network. Moreover, the metabolites in the same metabolic pathway are often associated with the same or similar disease. Based on these functional relationships between metabolites in the context of metabolic pathways, we here presented a pathway-based random walk method called PROFANCY for prioritization of candidate disease metabolites. Our strategy not only takes advantage of the global functional relationships between metabolites but also sufficiently exploits the functionally modular nature of metabolic networks. Our approach proved successful in prioritizing known metabolites for 71 diseases with an AUC value of 0.895. We also assessed the performance of PROFANCY on 16 disease classes and found that 4 classes achieved an AUC value over 0.95. To investigate the robustness of the PROFANCY, we repeated all the analyses in two metabolic networks and obtained similar results. Then we applied our approach to Alzheimer's disease (AD) and found that a top ranked candidate was potentially related to AD but had not been reported previously. Furthermore, our method was applicable to prioritize the metabolites from metabolomic profiles of prostate cancer. The PROFANCY could identify prostate cancer related-metabolites that are supported by literatures but not considered to be significantly differential by traditional differential analysis. We also developed a freely accessible web-based and R-based tool at http://bioinfo.hrbmu.edu.cn/PROFANCY.

Publications

  1. Prioritizing candidate disease metabolites based on global functional relationships between metabolites in the context of metabolic pathways.
    Cite this
    Shang D, Li C, Yao Q, Yang H, Xu Y, Han J, Li J, Su F, Zhang Y, Zhang C, Li D, Li X, 2014-01-01 - PloS one

Credits

  1. Desi Shang
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  2. Chunquan Li
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  3. Qianlan Yao
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  4. Haixiu Yang
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  5. Yanjun Xu
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  6. Junwei Han
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  7. Jing Li
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  8. Fei Su
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  9. Yunpeng Zhang
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  10. Chunlong Zhang
    Developer

    College of Bioinformatics Science and Technology, Harbin Medical University, China

  11. Dongguo Li
    Developer

    School of Biomedical Engineering, Capital Medical University

  12. Xia Li
    Investigator

    College of Bioinformatics Science and Technology, Harbin Medical University, China

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Summary
AccessionBT000185
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted ByXia Li