title: Pathway-based analysis tools for complex diseases: a review.
abstract: Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehensive understanding of the molecular mechanisms underlying complex diseases. Extensive studies utilizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods-the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available pathway-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are discussed. This review will provide a useful guide to dissect complex diseases.
authors.affiliation: Institute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
authors.forename: Lv
authors.initials: L
authors.lastname: Jin
authors.affiliation: Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
authors.forename: Xiao-Yu
authors.initials: XY
authors.lastname: Zuo
authors.affiliation: Community Health Service Management Center of Panyu District, Guangzhou 511400, China.
authors.forename: Wei-Yang
authors.initials: WY
authors.lastname: Su
authors.affiliation: Institute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
authors.forename: Xiao-Lei
authors.initials: XL
authors.lastname: Zhao
authors.affiliation: Department of Statistical Sciences, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China.
authors.forename: Man-Qiong
authors.initials: MQ
authors.lastname: Yuan
authors.affiliation: Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
authors.forename: Li-Zhen
authors.initials: LZ
authors.lastname: Han
authors.affiliation: Institute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhao
authors.affiliation: Institute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
authors.forename: Ye-Da
authors.initials: YD
authors.lastname: Chen
authors.affiliation: Institute for Medical Systems Biology, and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China; Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Department of Statistical Sciences, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China. Electronic address: raoshaoq@gdmc.edu.cn.
authors.forename: Shao-Qi
authors.initials: SQ
authors.lastname: Rao
mesh_terms: D016208:Databases, Factual; D004194:Disease / Q000235:genetics*; D053263:Gene Regulatory Networks; D006801:Humans; D015398:Signal Transduction; D012984:Software
keywords: Algorithms; Complex disease; Pathway-based analysis; Software and databases