ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations.
Bioinformatics
; 32(4): 549-56, 2016 Feb 15.
Article
em En
| MEDLINE
| ID: mdl-26508762
ABSTRACT
MOTIVATION 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. AVAILABILITY AND IMPLEMENTATION The ancGWAS package and documents are available at http//www.cbio.uct.ac.za/~emile/software.html.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
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Neoplasias da Mama
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Transdução de Sinais
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Polimorfismo de Nucleotídeo Único
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Mapeamento de Interação de Proteínas
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Estudo de Associação Genômica Ampla
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Genética Populacional
Tipo de estudo:
Risk_factors_studies
Limite:
Female
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Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article