metaCCA is a tool for the meta-analysis of genome-wide association study (GWAS) data based on summary statistics and using canonical correlation analysis.
GWAS study; Genotype and phenotype
Cichonska A, Rousu J, Marttinen P, Kangas AJ, Soininen P, Lehtimäki T, Raitakari OT, Järvelin MR, Salomaa V, Ala-Korpela M, Ripatti S, Pirinen M "metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis." Bioinformatics 2016; 32(13):1981-9 https://doi.org/10.1093/bioinformatics/btw052
PMID: 27153689
PMCID: PMC4920109
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J1, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M "Orchestrating high-throughput genomic analysis with Bioconductor." Nat Methods. 2015 Feb;12(2):115-21. https://doi.org/10.1038/nmeth.3252
PMID: 25633503
PMCID: PMC4509590
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J. "Bioconductor: open software development for computational biology and bioinformatics." Genome Biol. 2004;5(10):R80. Epub 2004 Sep 15. https://doi.org/10.1186/gb-2004-5-10-r80
PMID: 15461798
PMCID: PMC545600
If you find errors, please report here.
SECTIONS
TutorialsFind thousands of Bioinformatics and Life Science software tools and databases in the newly launched
Ads