Package: SIMLR
Version: 1.6.0
Date: 2018-03-09
Title: Title: SIMLR and CIMLR Multi-kernel LeaRning methods
Authors@R: c(person("Daniele", "Ramazzotti", role=c("aut", "cre"), email="daniele.ramazzotti@yahoo.com"),
             person("Bo", "Wang", role=c("aut"), email="bowang87@stanford.edu"),
             person("Luca", "De Sano", role=c("aut"), email="l.desano@campus.unimib.it"),
             person("Serafim", "Batzoglou", role=c("ctb")))
Maintainer: Daniele Ramazzotti <daniele.ramazzotti@yahoo.com>
Depends: R (>= 3.4),
Imports: parallel, Matrix, stats, methods, Rcpp, pracma, RcppAnnoy,
        RSpectra
Suggests: BiocGenerics, BiocStyle, testthat, knitr, igraph
Description: 
    In this package we provide implementations of both SIMLR and CIMLR. These methods were originally applied to single-cell and cancer genomic data, but they are in principle capable of effectively and efficiently learning similarities in all the contexts where diverse and heterogeneous statistical characteristics of the data make the problem harder for standard approaches. 
Encoding: UTF-8
LazyData: TRUE
License: file LICENSE
URL: https://github.com/BatzoglouLabSU/SIMLR
BugReports: https://github.com/BatzoglouLabSU/SIMLR
biocViews: Clustering, GeneExpression, Sequencing, SingleCell
RoxygenNote: 6.0.1
LinkingTo: Rcpp
NeedsCompilation: yes
VignetteBuilder: knitr
Packaged: 2018-05-01 01:10:33 UTC; biocbuild
Author: Daniele Ramazzotti [aut, cre],
  Bo Wang [aut],
  Luca De Sano [aut],
  Serafim Batzoglou [ctb]
Built: R 3.5.1; x86_64-apple-darwin14.5.0; 2018-10-27 16:14:11 UTC; unix
