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MCbiclust

MCbiclust

MCbiclust (Massively Correlated Biclustering) is a tool to cluster correlated gene expression in RNA-seq data sets. The MCbiclust algorithm finds the maximum strength correlation matrix and includes visualization tools.

Topic

Gene expression; Microarray experiment; RNA-seq; Statistics and probability

Details

  • Operation: Clustering
  • Software interface: Command-line user interface; Library
  • Language: R
  • Operating system: Linux; Mac OS X; Microsoft Windows
  • License: GNU GPL v2
  • Cost: Free
  • Version name: 1.10.0
  • Maturity: Stable
  • Credit: University College London COMPLeX-British Heart Foundation Fund; Biochemical and Biophysical Research Council; Wellcome Trust, UK; Association for Cancer Research (AIRC), Italy. Funding for open access charge: Wellcome Trust.
  • Contact: Robert Bentham robert.bentham.11 _at_ ucl.ac.uk
  • Collection: Bioconductor

Publications

Bentham RB, Bryson K, Szabadkai G "MCbiclust: a novel algorithm to discover large-scale functionally related gene sets from massive transcriptomics data collections." Nucleic Acids Res. 2017; 45(15):8712-8730 https://doi.org/10.1093/nar/gkx590
PMID: 28911113
PMCID: PMC5587796


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


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