SECA: SNP effect concordance analysis using genome-wide association summary results
Data(s) |
2014
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Resumo |
The genomics era provides opportunities to assess the genetic overlap across phenotypes at the measured genotype level; however, current approaches require individual-level genome-wide association (GWA) single nucleotide polymorphism (SNP) genotype data in one or both of a pair of GWA samples. To facilitate the discovery of pleiotropic effects and examine genetic overlap across two phenotypes, I have developed a user-friendly web-based application called SECA to perform SNP effect concordance analysis using GWA summary results. The method is validated using publicly available summary data from the Psychiatric Genomics Consortium. |
Formato |
application/pdf application/pdf |
Identificador | |
Publicador |
Oxford University Press |
Relação |
http://eprints.qut.edu.au/84317/7/84317_TrackChangesAccepted.pdf http://eprints.qut.edu.au/84317/8/84317_supp_mat.pdf DOI:10.1093/bioinformatics/btu171 Nyholt, Dale R. (2014) SECA: SNP effect concordance analysis using genome-wide association summary results. Bioinformatics, 30(14), pp. 2086-2088. |
Direitos |
Copyright 2014 Author |
Fonte |
School of Biomedical Sciences; Faculty of Health; Institute of Health and Biomedical Innovation |
Palavras-Chave | #article #computer program #genetic association #genomics #genotype #human #Internet #methodology #phenotype #single nucleotide polymorphism #Genome-Wide Association Study #Genomics #Genotype #Humans #Internet #Phenotype #Polymorphism, Single Nucleotide #Software |
Tipo |
Journal Article |