Package: Numero
Type: Package
Title: Statistical Framework to Define Subgroups in Complex Datasets
Version: 1.0.3
Date: 2017-12-01
Authors@R: c(person("Song", "Gao", role = "aut"),
              person("Stefan", "Mutter", role = "aut"),
              person("Aaron E.", "Casey", role = "aut"),
              person("Ville-Petteri", "Makinen", role = c("aut", "cre"),
                     email = "vpmakine@gmail.com"))
Description: High-dimensional datasets that do not exhibit a clear intrinsic clustered structure pose a challenge to conventional clustering algorithms. For this reason, we developed an unsupervised framework that helps scientists to better subgroup their datasets based on visual cues [Makinen V-P et al. (2011) J Proteome Res 11:1782-1790, <doi:10.1021/pr201036j>]. The framework includes the necessary functions to import large data files, to construct a self-organizing map of the data, to evaluate the statistical significance of the observed data patterns, and to visualize the results in scalable vector graphics.
License: GPL (>= 2)
Imports: Rcpp (>= 0.11.4)
LinkingTo: Rcpp
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2017-11-25 11:41:24 UTC; stefan.mutter
Author: Song Gao [aut],
  Stefan Mutter [aut],
  Aaron E. Casey [aut],
  Ville-Petteri Makinen [aut, cre]
Maintainer: Ville-Petteri Makinen <vpmakine@gmail.com>
Repository: CRAN
Date/Publication: 2017-12-01 11:48:16 UTC
Built: R 3.2.5; x86_64-apple-darwin13.4.0; 2017-12-02 08:44:49 UTC; unix
Archs: Numero.so.dSYM
