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Article: A gene-based test of association using canonical correlation analysis

TitleA gene-based test of association using canonical correlation analysis
Authors
Issue Date2012
Citation
Bioinformatics, 2012, v. 28, n. 6, p. 845-850 How to Cite?
AbstractMotivation: Canonical correlation analysis (CCA) measures the association between two sets of multidimensional variables. We reasoned that CCA could provide an efficient and powerful approach for both univariate and multivariate gene-based tests of association without the need for permutation testing.Results: Compared with a commonly used permutation-based approach, CCA (i) is faster; (ii) has appropriate type-I error rate for normally distributed quantitative traits; (iii) provides comparable power for small to medium-sized genes (<100 kb); (iv) provides greater power when the causal variants are uncommon; (v) provides considerably less power for larger genes (≥100 kb) when the causal variants have a broad minor allele frequency (MAF) spectrum. Application to a GWAS of leukocyte levels identified SAFB and a histone gene cluster as novel putative loci harboring multiple independent variants regulating lymphocyte and neutrophil counts. © The Author 2012. Published by Oxford University Press.
Persistent Identifierhttp://hdl.handle.net/10722/221328
ISSN
2015 Impact Factor: 5.766
2015 SCImago Journal Rankings: 4.643

 

DC FieldValueLanguage
dc.contributor.authorTang, Clara S.-
dc.contributor.authorFerreira, Manuel A R-
dc.date.accessioned2015-11-18T06:09:00Z-
dc.date.available2015-11-18T06:09:00Z-
dc.date.issued2012-
dc.identifier.citationBioinformatics, 2012, v. 28, n. 6, p. 845-850-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/221328-
dc.description.abstractMotivation: Canonical correlation analysis (CCA) measures the association between two sets of multidimensional variables. We reasoned that CCA could provide an efficient and powerful approach for both univariate and multivariate gene-based tests of association without the need for permutation testing.Results: Compared with a commonly used permutation-based approach, CCA (i) is faster; (ii) has appropriate type-I error rate for normally distributed quantitative traits; (iii) provides comparable power for small to medium-sized genes (<100 kb); (iv) provides greater power when the causal variants are uncommon; (v) provides considerably less power for larger genes (≥100 kb) when the causal variants have a broad minor allele frequency (MAF) spectrum. Application to a GWAS of leukocyte levels identified SAFB and a histone gene cluster as novel putative loci harboring multiple independent variants regulating lymphocyte and neutrophil counts. © The Author 2012. Published by Oxford University Press.-
dc.languageeng-
dc.relation.ispartofBioinformatics-
dc.titleA gene-based test of association using canonical correlation analysis-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1093/bioinformatics/bts051-
dc.identifier.scopuseid_2-s2.0-84859040141-
dc.identifier.volume28-
dc.identifier.issue6-
dc.identifier.spage845-
dc.identifier.epage850-
dc.identifier.eissn1460-2059-

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