ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations

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dc.contributor.authorChimusa, Emile R
dc.contributor.authorMbiyavanga, Mamana
dc.contributor.authorMazandu, Gaston K
dc.contributor.authorMulder, Nicola J
dc.date.accessioned2016-08-11T14:28:28Z
dc.date.available2016-08-11T14:28:28Z
dc.date.issued27
dc.date.updated2016-08-11T13:37:53Z
dc.description.abstractDespite numerous successful Genome-wide Association Studies (GWAS), detecting variants that have low disease risk still poses a challenge. GWAS may miss disease genes with weak genetic effects or strong epistatic effects due to the single-marker testing approach commonly used. GWAS may thus generate false negative or inconclusive results, suggesting the need for novel methods to combine effects of single nucleotide polymorphisms within a gene to increase the likelihood of fully characterizing the susceptibility gene. Results: We developed ancGWAS, an algebraic graph-based centrality measure that accounts for linkage disequilibrium in identifying significant disease sub-networks by integrating the association signal from GWAS data sets into the human protein–protein interaction (PPI) network. We validated ancGWAS using an association study result from a breast cancer data set and the simulation of interactive disease loci in the simulation of a complex admixed population, as well as pathway-based GWAS simulation. This new approach holds promise for deconvoluting the interactions between genes underlying the pathogenesis of complex diseases. Results obtained yield a novel central breast cancer sub-network of the human interactome implicated in the proteoglycan syndecan-mediated signaling events pathway which is known to play a major role in mesenchymal tumor cell proliferation, thus providing further insights into breast cancer pathogenesis.en_ZA
dc.identifier.apacitationChimusa, E. R., Mbiyavanga, M., Mazandu, G. K., & Mulder, N. J. (27). ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations. <i>Bioinformatics</i>, http://hdl.handle.net/11427/21201en_ZA
dc.identifier.chicagocitationChimusa, Emile R, Mamana Mbiyavanga, Gaston K Mazandu, and Nicola J Mulder "ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations." <i>Bioinformatics</i> (27) http://hdl.handle.net/11427/21201en_ZA
dc.identifier.citationChimusa, E. R., Mbiyavanga, M., Mazandu, G. K., & Mulder, N. J. (2015). ancGWAS: a Post Genome-wide Association Study Method for Interaction, Pathway, and Ancestry Analysis in Homogeneous and Admixed Populations. Bioinformatics, btv619.en_ZA
dc.identifier.issn1367-4803en_ZA
dc.identifier.ris TY - Journal Article AU - Chimusa, Emile R AU - Mbiyavanga, Mamana AU - Mazandu, Gaston K AU - Mulder, Nicola J AB - Despite numerous successful Genome-wide Association Studies (GWAS), detecting variants that have low disease risk still poses a challenge. GWAS may miss disease genes with weak genetic effects or strong epistatic effects due to the single-marker testing approach commonly used. GWAS may thus generate false negative or inconclusive results, suggesting the need for novel methods to combine effects of single nucleotide polymorphisms within a gene to increase the likelihood of fully characterizing the susceptibility gene. Results: We developed ancGWAS, an algebraic graph-based centrality measure that accounts for linkage disequilibrium in identifying significant disease sub-networks by integrating the association signal from GWAS data sets into the human protein–protein interaction (PPI) network. We validated ancGWAS using an association study result from a breast cancer data set and the simulation of interactive disease loci in the simulation of a complex admixed population, as well as pathway-based GWAS simulation. This new approach holds promise for deconvoluting the interactions between genes underlying the pathogenesis of complex diseases. Results obtained yield a novel central breast cancer sub-network of the human interactome implicated in the proteoglycan syndecan-mediated signaling events pathway which is known to play a major role in mesenchymal tumor cell proliferation, thus providing further insights into breast cancer pathogenesis. DA - 27 DB - OpenUCT DP - University of Cape Town J1 - Bioinformatics LK - https://open.uct.ac.za PB - University of Cape Town PY - 27 SM - 1367-4803 T1 - ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations TI - ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations UR - http://hdl.handle.net/11427/21201 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/21201
dc.identifier.vancouvercitationChimusa ER, Mbiyavanga M, Mazandu GK, Mulder NJ. ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations. Bioinformatics. 27; http://hdl.handle.net/11427/21201.en_ZA
dc.languageengen_ZA
dc.publisherOxford University Pressen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.sourceBioinformaticsen_ZA
dc.source.urihttp://bioinformatics.oxfordjournals.org/
dc.titleancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populationsen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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