metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Cu...

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Veröffentlicht in:	Bioinformatics Jg. 32; H. 13; S. 1981 - 1989
Hauptverfasser:	Cichonska, Anna, Rousu, Juho, Marttinen, Pekka, Kangas, Antti J., Soininen, Pasi, Lehtimäki, Terho, Raitakari, Olli T., Järvelin, Marjo-Riitta, Salomaa, Veikko, Ala-Korpela, Mika, Ripatti, Samuli, Pirinen, Matti
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Oxford University Press 01.07.2016
Schlagworte:	Algorithms Bioinformatics Computational Biology - methods Correlation analysis Genome-Wide Association Study Genotype Humans Multivariate Analysis Original Papers Phenotype Polymorphism, Single Nucleotide Samples Shrinkage Statistical methods Statistics Summaries
ISSN:	1367-4803, 1367-4811, 1460-2059
Online-Zugang:	Volltext
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