Package: ADaCGH2
Version: 2.27.0
Date: 2018-07-16
Title: Analysis of big data from aCGH experiments using parallel
        computing and ff objects
Author: Ramon Diaz-Uriarte <rdiaz02@gmail.com> and Oscar M. Rueda <rueda.om@gmail.com>. Wavelet-based aCGH smoothing code from Li Hsu <lih@fhcrc.org> and Douglas Grove <dgrove@fhcrc.org>. Imagemap code from Barry Rowlingson <B.Rowlingson@lancaster.ac.uk>. HaarSeg code from Erez Ben-Yaacov; downloaded from <http://www.ee.technion.ac.il/people/YoninaEldar/Info/software/HaarSeg.htm>. 
Maintainer: Ramon Diaz-Uriarte <rdiaz02@gmail.com>
Depends: R (>= 3.2.0), parallel, ff, GLAD
Imports: bit, ffbase, DNAcopy, tilingArray, waveslim, cluster, aCGH,
        snapCGH
Suggests: CGHregions, Cairo, limma
Enhances: Rmpi
Description: Analysis and plotting of array CGH data. Allows usage of
	     Circular Binary Segementation, wavelet-based smoothing 
	     (both as in Liu et al., and HaarSeg as in Ben-Yaacov and Eldar), 
	     HMM, BioHMM, GLAD, CGHseg. Most computations are
	     parallelized (either via forking or with clusters, including
	     MPI and sockets clusters) and use ff for storing data.
biocViews: Microarray, CopyNumberVariants
LazyLoad: Yes
License: GPL (>= 3)
URL: https://github.com/rdiaz02/adacgh2
git_url: https://git.bioconductor.org/packages/ADaCGH2
git_branch: master
git_last_commit: a25d4f4
git_last_commit_date: 2019-10-29
Date/Publication: 2019-11-08
NeedsCompilation: yes
Packaged: 2019-11-09 02:15:25 UTC; biocbuild
Built: R 4.0.0; i386-w64-mingw32; 2019-11-09 09:10:44 UTC; windows
Archs: i386, x64
