MultiMeta: An R package for meta-analyzing multi-phenotype genome-wide association studies

Bioinformatics

Volumn 31, Issue 16, 2015, Pages 2754-2756

  Vuckovic, D ^a   Gasparini, P ^a,b   Soranzo, N ^c,d   Iotchkova, V ^c,e  

^a UNIVERSITY OF TRIESTE   (Italy)

^b INSTITUTE FOR MATERNAL AND CHILD HEALTH IRCCS BURLO GAROFOLO   (Italy)

^c WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

^d UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^e WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

GENE LOCUS; GENOME-WIDE ASSOCIATION STUDY; HUMAN; META ANALYSIS (TOPIC); MULTIVARIATE ANALYSIS; PHENOTYPE; PROCEDURES; SOFTWARE;

GENETIC LOCI; GENOME-WIDE ASSOCIATION STUDY; HUMANS; META-ANALYSIS AS TOPIC; MULTIVARIATE ANALYSIS; PHENOTYPE; SOFTWARE;

EID: 84939534434     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv222     Document Type: Article

References (5)

1. Hindorff, L. et al. (2014) A Catalog of Published Genome-Wide Association Studies. http://www. genome. gov/GWAStudies/ [August 2014, date last accessed]
2. Korte, A. et al. (2012) A mixed-model approach for genome-wide association studies of correlated traits in structured populations. Nat. Genet. , 44, 1066-1071.
3. Sanna, S. et al. (2008) Common variants in the GDF5-UQCC region are associated with variation in human height. Nat. Genet. , 40, 198-203.
4. Willer, C. J. et al. (2010) METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics, 26, 2190-2191.
5. Zhou, X. and Stephens, M. (2014) Efficient multivariate linear mixed model algorithms for genome-wide association studies. Nat. Methods, 11, 407-409.