Please use this identifier to cite or link to this item:
Title: Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions
Authors: Kao, PYP 
Leung, KH 
Chan, LWC 
Yip, SP 
Yap, MKH 
Keywords: Complex disease; Genome-wide association study (GWAS); Interaction; Multi-omics; Pathway analysis; Rare variants
Issue Date: Feb-2017
Publisher: Elsevier
Source: Biochimica et biophysica acta. General subjects, Feb. 2017, v. 1861, no. 2, p. 335-353 How to cite?
Journal: Biochimica et biophysica acta. General subjects 
Abstract: Background Genome-wide association studies (GWAS) is a major method for studying the genetics of complex diseases. Finding all sequence variants to explain fully the aetiology of a disease is difficult because of their small effect sizes. To better explain disease mechanisms, pathway analysis is used to consolidate the effects of multiple variants, and hence increase the power of the study. While pathway analysis has previously been performed within GWAS only, it can now be extended to examining rare variants, other “-omics” and interaction data. Scope of review 1. Factors to consider in the choice of software for GWAS pathway analysis. 2. Examples of how pathway analysis is used to analyse rare variants, other “-omics” and interaction data. Major conclusions To choose appropriate software tools, factors for consideration include covariate compatibility, null hypothesis, one- or two-step analysis required, curation method of gene sets, size of pathways, and size of flanking regions to define gene boundaries. For rare variants, analysis performance depends on consistency between assumed and actual effect distribution of variants. Integration of other “-omics” data and interaction can better explain gene functions. General significance Pathway analysis methods will be more readily used for integration of multiple sources of data, and enable more accurate prediction of phenotypes.
ISSN: 0304-4165
EISSN: 1872-8006
DOI: 10.1016/j.bbagen.2016.11.030
Rights: © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (
The following publication Kao, P. Y., Leung, K. H., Chan, L. W., Yip, S. P., & Yap, M. K. (2016). Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions. Biochimica et Biophysica Acta (BBA)-General Subjects, 1861 (2), 335-353 is available at
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Kao_Complex_Diseases_GWAS.pdf1.05 MBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Aug 14, 2017

Page view(s)

Last Week
Last month
Checked on Aug 13, 2017


Checked on Aug 13, 2017

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.